A multi-mode resource-constrained project scheduling model with bi-random coefficients for drilling grouting construction project 2 2 To improve the construction efficiency of the Longtan Hydropower Project, this paper studies the multi-mode resourceconstrained project scheduling problem in its Drilling Grouting Construction Project. A multiple objective decision making model with bi-random coefficients is first proposed for this practical problem to cope with hybrid uncertain environment where twofold randomness exists. Subsequently, to deal with the uncertainties, the chance constraint operator is introduced and the equivalent crisp model is derived. Furthermore, the particular nature of our model motivates us to develop particle swarm ptimization algorithm for the equivalent crisp model. Finally, the results generated by computer highlight the performances of the proposed model and algorithm in solving large-scale practical problems. 1 13 2012/04/10 1391/1/22 2013/03/16 1391/12/26 ZH. ZHANG ZH. ZHANG Nanjing University of Science and Technology CHINA zhangzhe@njust.edu.cn J. XU J. XU Sichuan University CHINA Optimization model Large scale scheduling Resource-constrained Bi-random coefficients Multi-mode [1] Brucker, P., Drexl, A. and et al., Resource-constrained project scheduling: notation, classification, models, and methods, European Journal of Operational Research, 1999; 112(1), 3-41.##[2] Slowinski, R., Soniewicki, B., Weglarz, J., Dss for multiobjective project scheduling, European Journal of Operational Research, 1994; 79, 220-229.##[3] Demeulemeester, E., Herroelen, W., Project scheduling: A research handbook, Boston: Kluwer Academic Publishers (2002).##[4] Kolisch, R. and Padman, R., An integrated survey of deterministic project scheduling, Omega, 2001; 29, 249-272.##[5] Nudtasomboon, N., Randhawa, S., Resource-constrained project scheduling with renewable and non-renewable resources and time-resource tradeoffs, Computers & Industrial Engineering, 1997; 32(1), 227-242.##[6] Drexl, A., Grunewald, J., Non-preemptive multi-mode resource-constrained project scheduling, IIE Transactions, 1993; 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50, 55-65.##[12] He, Z. and Xu, Y., Multi-mode project payment scheduling problems with bonus penalty structure, European Journal of Operational Research, 2008; 189, 1191-1207.##[13] Jarboui, B., Damak, N., Siarry, P., Rebai, A., A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems, Applied Mathematics and Computation, 2008; 195, 299-308.##[14] Peteghem, V. and Vanhoucke, M., A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem, European Journal of Operational Research, 2010; 201, 409-418.##[15] Aytug, H., Lawley M., and et al., Executing production schedules in the face of uncertainties: A review and some future directions, European Journal of Operational Research, 2005; 161, 86-110.##[16] Bidot, J., Thierry, V. and et al., A theoretic and practical framework for scheduling in a stochastic environment, Journal of Scheduling, 2008; 10, 41-65.##[17] Herroelen, W., Leus, R., Project scheduling under uncertainty: Survey and research potentials, European Journal of Operational Research, 2005; 165, 289-306.##[18] Vonder, V., Demeulemeester, S., and et al., The use of buffers in project management: The trade-off between stability and makespan, International Journal of Production Economics, 2005; 97, 227-240.##[19] Yagi, J., Arai, E., and et al., Action-based union of the temporal opposites in scheduling: non-deterministic approach, Automation in Construction, 2003; 12, 321-329.##[20] Peng, J. and Liu, B., Birandom variables and birandom programming, Computers and Industrial Engineering, 2007; 53, 433-453.##[21] Xu, J., Zhou X., A class of multi-objective expected value decision-making model with bi-random coefficients and its application to flow shop scheduling problem, Information Sciences, 2009; 179, 2997-3017.##[22] Yan L., Chance-constrained Portfolio Selection with Bi-random Returns, Modern Applied Science, 2009; 3(4), 161-165.##[23] Xu, J., Ding C., A class of chance constrained multiobjective linear programming with birandom coefficients and its application to vendors selection, International Journal of Production Economics, 2011; 131(2), 709-720.##[24] Xu, J., Zhang, Z., and Mookerjee, V., Applying Bi-Random MODM Model to Navigation Coordinated Scheduling: A Case Study of Three Gorges Project, Transport, 2011; Inpress.##[25] Zhang, Z., Applying improved particle swarm optimization algorithm to bi-level linear programming problem with bi-random coefficients, Proceedings of The Fifth International Conference on Management Science and Engineering Management, 2011; 147-152.##[26] Zhang, Z., Bi-Level Multi-Objective Resource-Constrained Project Scheduling Models under complex random phenomena and the Application, Doctoral Dissertation, Sichuan University (In Chinese), 2011.##[27] Liu, B., Theory and Practice of Uncertain Programming, New York: Physica Verlag (2002).##[28] Charnes, A., Cooper, W., Chance-constrained programming, Management Science, 1959; 6, 73-79.##[29] Boctor, F., A new and effcient heuristic for scheduling projects with resource restrictions and multiple execution modes, European Journal of Operational Research, 1996; 90, 349-361.##[30] Ozdamar, L, A genetic algorithm approach to a general category project scheduling problem, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 1999; 29, 44-59.##[31] Sprecher, A., Resource-constrained project scheduling: Exact methods for the multi-mode case, Lecture Notes in Economics and Mathematical Systems, Berlin: Springer (1994).##[32] Sprecher, A. and Drexl, A., Multi-mode resource-constrained project scheduling by a simple, general and powerful sequencing algorithm, European Journal of Operational Research, 1998; 107, 431-450.##[33] Kolisch, R. and Drexl, A., Local search for nonpreemptive multi-mode resource-constrained project scheduling, IIE Transactions, 1997; 29, 987-999.##[34] Mori, M. and Tseng, C., A genetic algorithm for multi-mode resource constrained project scheduling problem, European Journal of Operational Research, 1997; 100, 134-141.##[35] Zhang, H., Tam, C., and Li, H., Multimode project scheduling based on particle swarm optimization, Computer-Aided Civil and Infrastructure Engineering, 2005; 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Modeling quality management in construction projects 2 2 This research presents a dynamic mathematical system for modeling and simulating the quality management process in construction projects. Through sets of cause and effect feedback loops, all factors that internally and externally affect the quality management process are addressed. The proposed system integrates fuzzy logic with system dynamics simulation scheme to consider the uncertainties associated with the model parameters and estimation of the extra cost and time due to quality defects. Quantification of the consequences of the quality failures is performed based on the α-cut representation of fuzzy numbers and interval analysis. The proposed approach is efficient in modeling and analyzing a quality management process which is complex and dynamic in nature and involves various uncertainties. The proposed approach is implemented in a real submarine water supply pipe line project in order to evaluate its applicability and performance. The negative impacts resulting from quality failures are simulated. These negative impacts are mitigated by the implementation of alternative solutions. 14 22 2012/04/102011/11/16 1390/8/25 2013/03/162013/04/10 1392/1/21 F. Nasirzadeh F. Nasirzadeh Payame Noor University, Iran f.nasirzadeh@gmail.com M. Khanzadi M. Khanzadi Iran University of Science and Technology Iran khanzadi@iust.ac.ir A. Afshar A. Afshar Iran University of Science and Technology Iran a_afshar@iust.ac.ir S. Howick S. Howick Starthclyde University United Kingdom susan.howick@strath.ac.uk Fuzzy logic Modeling Quality management Simulation System dynamics [1] Arditi, D. and Murat, G.: 1997. Total quality management in the construction process. International Journal of Project Management, 15(4), 235-243.##[2] Ashford, J. L.: 1992, The management of quality in construction. E & F Spon, London, ##[3] Construction Industry Development Agency and Masters Builders Australia (CIDA): 1995. Measuring up or muddling through: best practice in the Australian non-residential construction industry, Sydney, Australia, 59–63.##[4] Burati, J., Farrington, J., and Ledbetter, W.: 1992. Causes of quality deviations in design and construction. J. Constr. Eng. Manage., 118(1), 34–49.##[5] Love, P., and Li, H.: 2000. Quantifying the causes and costs of rework in construction. International Journal of Construction Management and Economics. 18(4), 479–490.##[6] Love, P., Mandal, P., and Li, H.: 1999. Determining the casual structure of rework in construction. International Journal of Construction Management and Economics. 17(4), 505–517.##[7] Rodrigues, A., and Bowers, J.: 1996. The role of system dynamics in project management. International Journal of Project Management. 14(4), 213± 20.##[8] Williams, T., Eden, C., Ackerman, F., and Tait, A.: 1996. Vicious circles of parallelism. International Journal of Project Management. 13(3), 151-155.##[9] Ford, D., and Sterman, D.: 1998. Dynamic Modeling of Product Development Processes. Sys. Dyn. Revrg. 14, 31-68. ##[10] Forrester, J.: 1961. Industrial Dynamics. MIT Press, Cambridge, US.[11] Lee, S., Peña-Mora, F., and Park, M.: 2005. Quality and Change Management Model For Large Scale Concurrent Design and Construction Projects. J. Constr. Eng. Manage., 131(8), 890-902.##[12] Juran, J. M.: 1988. Quality Control Handbook, 4th ed. McGraw-Hill, New York. ##[13] Zadeh, L.A.: 1965. Fuzzy sets. Inf. Control, 338–353.##[14] Mamdani, E. H., and Assilian, S: 1975. An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man-Mach. Stud., 7(1), 1–13. ##[15] Zimmermann, H. J.: 2001. Fuzzy Set Theory and it\'s Application, fourth edition. Kluwer Academic Pub.##[16] Nasirzadeh, F., Afshar, A., and Khanzadi, M.: 2008. Dynamic risk analysis in construction projects, Canadian Journal of Civil Engineering. 35, 820–831.##[17] Nasirzadeh, F., Afshar, A., Khanzadi, M., and Howick, S.: 2008. Integrating system dynamics and fuzzy logic modeling for construction risk management. International Journal of Construction Management and Economics. 26, 1197–1212.##[18] Nasirzadeh, F. & Afshar, A. and Khanzadi, M.: 2008. ”System Dynamics Approach to Construction Project Risk Management”, International Journal of Civil Engineering, Vol. 6(2). 120-131.## ##

Development of Web-based Design Management System through User Participatory Design and Use-case Modeling 2 2 Construction industry consists of several phases in which a variety of stakeholders are involved. As construction projects are becoming larger, more complex and more diverse, the design phase has been more important factor for the success of projects than ever before. However, it is considered that most of design work occurred in actual design process is intangible. Such recognition makes the design phase more unsystematic and arbitrary, which finally weakens the competitiveness of whole project. In order to solve these problems, this study developed a web-based system for integrated design management (IDMS) which consists of 8 modules including design document, schedule, quality, and building permit management. This section is intended to validate the system implementation and its effectiveness. Two characteristics have made this research significantly different from previous studies. First of all, users of the system including architects and other design professionals were continuously involved starting from the development phase to the validation phase. The other unique characteristic is that the actual design project was applied as a test bed in the final verification stage. The research team applied the actual data which had been generated while each business process, and verified the effectiveness of system implementation. The authors expect that such a user-centered approach enable the system more robust and effective. 23 32 2012/04/102011/11/162011/02/10 1389/11/21 2013/03/162013/04/102013/03/16 1391/12/26 J. S. Yi J. S. Yi Ewha University Korea jsyi@ewha.ac.kr C. W. Koo C. W. Koo HanmiParsons Co., Ltd. Korea cwkoo@hanmiparsons.com S. H. Park S. H. Park HanmiParsons Co., Ltd. Korea parksh@hanmiparsons.com O. K. Kwon O. K. Kwon HanmiParsons Co., Ltd. Korea okkwon@hanmiparsons.com management web-based system participatory design use-case modeling scenario-based method [1] Austin, S., Baldwin, A., Newton, A. (1996) A data flow model to plan and manage the building design process. Journal of Engineering Design, Vol. 7, No. 1, pp.3-25.##[2] Ballard, G., Howell, G. (1998a) Shielding production: an essential step in production control. Journal of Construction Engineering and Management, Vol. 124, No. 1, pp.18-24.##[3] Ballard, G. (1998b) Positive vs negative iteration in design, in Proceedings of the 8th Annual Conference of the International Group for Lean Construction, Brighton, UK, July, 1998.##[4] Lottaz, C., Cle` ment, D.E., Faltings, B.V. and Smith, L.F.C. (1999) Constraint-based support for collabortion in design and construction. Journal of Computing in Civil Engineering, 23–35.##[5] The American Institute of Architects (AIA) (2007a). Integrated Project Delivery : A Working Definition.##[6] The American Institute of Architects (AIA) (2007b). Integrated Project Delivery : A Guide.##[7] Koskela, L. (1992) Application of the New Production Philosophy to Construction. Technical Report 72, CIFE, Stanford University, Stanford, CA.##[8] Taguchi, G., Chowdhury, S. and Taguchi, S. (2000) Robust Engineering, McGraw-Hill, New York.##[9] Ballard, G., Harper, N. and Zabelle, T. (2002) Learning to see work flow. Engineering, Construction and Architectural Management, (in press).##[10] The American Institute of Architects (AIA) (2002). The Architect\'s Handbook of Professional Practice, John Wiley & Sons, Inc.##[11] Ayas, K. (1996) Professional project management: a shift towards learning and a knowledge creating structure. International Journal of Project Management, Elsevier, Vol. 14, No. 3, pp. 131-136.##[12] Koskela, LJ, Huovila, P and Leinonen, J (2002) Design management in building construction: from theory to practice. Journal of Construction Research, Vol. 3, No. 1, pp. 1-16.##[13] Colin Gray and Will Hughes (2001) Building Design Management, Butterworth-Heinemann. p. 43-49.##[14] Tzortzopoulos, P., and Formoso, C.T (1999) Considerations on Application of Lean Construction Principles to Design Management. Proceedings, International Group for Lean Construction-7, 335- 344.##[15] Sobek, D. K., II and Ward, A.C. (1996) Principles from Toyota’s set-based concurrent engineering process, in Proceedings of ASME Design Engineering Technical Conferences and Computers in Engineering Conference, 18–22 August, Mechanical Engineering, Irvine, CA, July 1996, 118(7), 78–81.##[16] Ohno, T. (1988) The Toyota Production System: Beyond Large Scale Production, author with Setsuo Mito, trans. Joseph P. Schmelzis, Productivity Press, Cambridge, MA.##[17] Koo, C.W. (2009) Understanding of the Integrated Design Management. 19th Issue Report, Construction Strategy Research Institute, HanmiParsons Co., Ltd.##[18] Austin, S., Baldwin, A., Li, B. and Waskett, P. (1999) Analytical Design Planning Technique : a model of the detailed building design process. Design Studies, Vol. 20, No. 3, pp.279-296.##[19] Ballard, G. (2000) The last planner system of production control. PhD dissertation, Civil Engineering, University of Birmingham, Birmingham.##[20] Austin, S., Baldwin, A., Li, B. and Waskett, P. (2000) Analytical design planning technique (ADePT): a dependency structure matrix tool to schedule the building design process. Construction Management & Economics, Vol. 18, pp.173-182.##[21] Choo, H.J., Tommelein, I.D., Ballard, G., and Zabelle, T.R. (1999) Work-Plan: constraint-based database for work package scheduling, ASCE, Journal of Construction Engineering and Management, Vol. 125, No. 3, pp.151-160.##[22] Choo, H.J., Hammond, J., Tommelein, I.D., Austin, S., and Ballard, G. (2004) DePlan: A tool for integrated design management. Automation in Construction, Vol. 13, No. 3, pp.313-326.##[23] Krishnamurthy, K., Law, K.H. (1995) Change Management for Collaborative Engineering. Computing in Civil Engineering, Proceedings of the Second Congress held in Conjunction with A/E/C System.##[24] D.K.H. Chua, A. Tyagi, S. Ling, S.H. Bok (2003). Process-Parameter-Interface Model for Design Management. Journal of construction engineering and management, Vol. 129, No. 6, pp. 653-663.##[25] Choi, Y.J., Yi, J.S., and Bae, J.I (2006) A Study on Selecting Key Factor of Design Management Considering Current Situation of Design Process. Korea Institute of Construction Engineering and Management, 22(10), 111-118.## ##

Optimal resource allocation in urban transportation networks considering capacity reliability and connectivity reliability: a multi-objective approach 2 2 Since the 1990’s, network reliability has been considered as a new index for evaluating transportation networks under uncertainty. A large number of studies have been revealed in the literature in this field, which are mostly dedicated to developing relevant measures that can be utilized for the evaluation of vulnerable networks under different sources of uncertainty, such as daily traffic flow fluctuations, natural disasters, weather conditions, and so fourth. This paper addresses the resource allocation problem in vulnerable transportation networks, in which multiple performance reliability measures should be met at their desired levels, while the overall cost of upgrading links’ performances should be minimized simultaneously. For this purpose, a new approach has been considered to formulate the two well-known performance measures, connectivity and capacity reliability, along with their application in a bi-objective nonlinear mixed integer goal programming model. In order to take into account the uncertain conditions of supply, links’ capacities have been assumed to be random variables and follow normal distribution functions. A computationally efficient method has been developed that allows calculating the network-wise performance indices simply by means of a set of functions of links’ performance reliabilities. Using this approach, as the performance reliability of links are themselves functions of the random links’ capacities, they can be simply calculated through numerical integration. To achieve desirable levels for both connectivity reliability and capacity reliability (as network-wise performance reliability measures) two distinct objectives have been considered. One of the objectives seeks to maximize each of the measures regardless of what is happening to the other objective function which minimizes the budget. Since optimization models with two conflicting objectives cannot be solved directly, the well-known goal attainment multi-objective decision-making (MODM) approach has been adapted to formulate the model as a single objective model. Then the resultant single objective model has been solved through the generalized gradient method, which is a straightforward solution algorithm coded in existing commercial software such as MATLAB programming software. To show the applicability of the proposed model, numerical results are provided for a simple network. Also, to show the sensitiveness of the model to decision maker’s direction weights, the results of sensitivity analysis are presented.. 33 42 2012/04/102011/11/162011/02/102010/08/30 1389/6/8 2013/03/162013/04/102013/03/162013/03/16 1391/12/26 A. Shariat Mohaymany A. 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J., Tu, H.: 2008, Travel time unreliability on freeways: Why measures based on variance tell only half the story, Transportation Research Part A 42, 258–277.##Lomax, T., Scrank, D., Turner S., Margiotta R.: 2003, Selecting Travel Time Reliability, Texas Transportation Institute and Cambridge Systematics, Inc.##Chen, A., H. Yang, H.K. Lo, Tang, W.H.: 1999, A Capacity Related Reliability for Transportation Networks, Journal of Advanced Transportation 33, 183-200.##Yang, H., Lo, H.K., Tang, W.H.: 2000, Travel time versus capacity reliability of a road network, In Reliability of Transport Networks (edt. M. Bell and C. Cassir), Research Studies Press Ltd., 191-138.##Shariat Mohaymany, A., Babaei, M.: 2010, An Approximate Reliability Evaluation Method for Improving Transportation Network Performance, Transport 25(2),195-202. ##Shariat Mohaymany, A., Babaei, M.: 2007, A New Technique for Evaluating the Performance Reliability of Transportation Network, Proceedings of the third International Symposium on Transportation Reliability (INSTR2007), Netherlands.##Chen, A., Zhou, Z., Chootinan, P., Ryu, S., Yang, C., Wong, S. 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G. H.: 1998, Models and algorithms for road network design: a review and some new developments, Transport Reviews 18 (3), 257-278.##Figuira, J., Greco, S., Ehrgott, M.: 2005, Multi Criteria Decision Analysis: State of the Art Surveys, Springer.## ##

Bus fleet optimization using genetic algorithm a case study of Mashhad 2 2 In this paper, a new approach was presented for bus network design which took the effects of three out of four stages of the bus planning process into account. The presented model consisted of three majors steps 1- Network Design Procedure (NDP), 2- Frequency Determination and Assignment Procedure (FDAP), and 3- Network Evaluation Procedure (NEP). Genetic Algorithm (GA) was utilized to solve this problem since it was capable of solving large and complex problems. Optimization of bus assignment at depots is another important issue in bus system planning process which was considered in the presented model. In fact, the present model was tested on Mandl’s bus network which was a benchmark in Swiss network and was initially employed by Mandl and later by Baaj, Mahmassani, Kidwai, Chakroborty and Zhao. Several comparisons indicated that the model presented in this paper was superior to the previous models. Meanwhile, none of the previous approaches optimized depots assignment. Afterwards, sensitivity analysis on GA parameters was done and calculation times were presented. Subsequently the proposed model was evaluated thus, Mashhad bus network was designed using the methodology of the presented model. 43 52 2012/04/102011/11/162011/02/102010/08/302010/04/24 1389/2/4 2013/03/162013/04/102013/03/162013/03/162013/03/17 1391/12/27 Sh. Afandizadeh Sh. Afandizadeh Iran University of Science and Technology Iran zargari@iust.ac.ir H. Khaksar H. Khaksar Iran University of Science and Technology Iran khaksar@iust.ac.ir N. Kalantari N. Kalantari Iran University of Science and Technology Iran kalantari@iust.ac.ir Assignment Genetic Network design [1] Transportation Research-B, 1986, Bus Network Design, Vol. 20B, No 4. PP 331-344, 1986.##[2] Fan, W., Machemehl, R.B., “Optimal Transit Route Network Design Problem: Algorithms, Implementations, and Numerical Results”, Research Report SWUTC/04/167244-1, Southwest Region University Transportation Center for Transportation Research University of Texas at Austin, 2004.##[3] Lampkin, W. and Saalmans. P.D., “The Design of Routes, Service Frequencies and Schedules for a Municipal Bus Undertaking: A Case Study”, Operation Research Quarterly, No. 18, pp. 375-397, 1967.##[4] Silman, L.A., Barzily, Z., and Passy, U. “Planning the Route System for Urban Buses”, Computers and Operations Research, Vol. 1, pp 201-211, 1974.##[5] Mandl, C.E., “Evaluation and Optimization of Urban Public Transport Networks”, European Journal of Operational Research, Vol. 6, pp 31-56, 1980.##[6] Dubois, D., Bell, G., and Llibre, M., “A Set of Methods in Transportation Network Synthesis and Analysis”, Journal of Operations Research Society, Vol. 30, pp797-808, 1979.##[7] LeBlanc. L.J., “Transit System Network Design”, Transportation Research Part B, Vol. 22, No. 5, pp 383-390, 1988.##[8] Van Nes, R., Hamerslag, R., and Immer, B.H., “The Design of Public Transport Networks”, Transportation Research Record, No. 1202, Transportation Research Board, Washington, D.C., pp 74-83, 1988. ##[9] Baaj, M.H. and Mahmassani, H.S., “An AI-Based Approach for Transit Route System Planning and Design”, Journal of Advanced Transportation, Vol. 25, No. 2, pp 187-210, 1991.##[10] Ceder, A, Israeli, Y., “User and Operator Perspectives in Transit Network Design”, Transportation Research Record, No. 1623, 1998.##[11] Pattnaik, S.B., Mohan, S. and Tom, V.M, “Urban Bus Transit Network Design Using Genetic Algorithm”, Journal of Transportation Engineering, Vol. 124, No. 4, pp 368-375, 1998.##[12] Tom, V.M. and Mohan, S., “Transit Route Network Design Using Frequency Coded Genetic Algorithm”, Journal of Transportation Engineering, Vol. 129, No. 2, pp 186-195, 2003.##[13] Chakroborty, P., Wivedi, T., “Optimal route network design for transit system using genetic algorithms”, Journal of Engineering Optimization, Vol .34(1), pp.83-100, 2002.##[14] Ngamchai, S. and Lovell, D.J., “Optimal Time Transfer in Bus Transit Route Network Design using a Genetic Algorithm,” ASCE Journal of Transportation Engineering, Vol. 129, No. 5, P 510-521, 2003.##[15] Zhao, F., Gan, A., “Optimization of Transit Network to Minimize Transfers”, Final Report BD015-02, Research Office Florida Department of Transportation, 2003. ## [16] Han, J., Lee, S., Kim, J., “Meta-Heuristic Algorithms for a Transit Route Design”, 16th Mini-EURO Conference, Artificial Intelligence in Transportation, September 13-16, 2005, Poznan, Poland, 2005.## [17] Zhao, F., “Large-Scale Transit Network Optimization by Minimizing User Cost and Transfers”, Journal of Public Transportation, Vol. 9, No. 2, 2006, pp 107-129, 2006.##[18] Zhao, F., Zeng, X., “Optimization of transit route network, vehicle headways and timetables for large-scale transit networks”, European Journal of Operational Research, Vol. 186, pp 841–855, 2008.##[19] Sh. Afandizadeh, S. A. H Zahabi, N. Kalantari, “Estimating the parameters of Logit Model using simulated annealing algorithm: case study of mode choice modeling of Isfahan”, International Journal of Civil Engineerng. Vol. 8, No. 1, March 2010.##[20] Sh. Afandizadeh, Reza Taromi, “Selecting an Optimum Configuration of Urban One-Way and Two-Way Streets Using Genetic Algorithms”, International Journal of Civil Engineering, Vol. 4, No. 3, September 2006.##[21] Ceder, A., Methods for creating bus timetables, Transportation Research, Vol. 21A, No. 1, pp. 59-83, 1986.## ##

Estimation of delay at signalized intersections for mixed traffic conditions of a developing country 2 2 Delay is one of the principal measures of performance used to determine the Level of Service (LOS) at signalized intersections and several methods have been widely used to estimate vehicular delay. Very few studies only have been carried out to estimate delay at signalized intersections under mixed traffic conditions prevailing in developing countries like India. In the present study, various problems associated with delay estimation under mixed traffic conditions in a developing country (India) and the methods to over come them were discussed and an attempt was made to improve the accuracy estimating the same. Five isolated signalized intersections from a fast developing industrial city located in TamilNadu, India were chosen for the study. Site specific PCU values were developed considering the static and dynamic characteristics of vehicles. Saturation flow was also directly measured in the field for the prevailing roadway, traffic and signalized conditions and expressed in PCU/h. Control delay was also measured following HCM 2000 guidelines. Later, this was compared with that estimated from the theoretical delay model. Even after taking several measures, good correlation between observed and predicted delay could not be obtained. Therefore, in the present scenario field measured control delay was taken into account to define LOS. A new criteria for Indian cities recently published in the literature was used to assign LOS grades of study intersections and found to be better reflecting the field conditions. 53 59 2012/04/102011/11/162011/02/102010/08/302010/04/242011/08/31 1390/6/9 2013/03/162013/04/102013/03/162013/03/162013/03/172013/03/16 1391/12/26 R. Prasanna Kumar R. Prasanna Kumar SASTRA UNIVERSITY India prasanna@civil.sastra.edu G. Dhinakaran G. Dhinakaran SASTRA UNIVERSITY India gd@civil.sastra.edu delay signalized intersections mixed traffic PCU saturation Flow LOS 1. SU Yuelong, WEI Zheng, CHENG Sihan, YAO Danya, ZHANG Yi , LI Li (2009), “Delay Estimates of Mixed Traffic Flow at Signalized Intersections in China” Tsinghua Science and Technology, Volume 14, Number 2, April 2009.##2. Yusria Darma, Mohamed Rehan Karim, Jamilah Mohamad and Sulaiman Abdullah,“ Control Delay Variability at Signalized Intersection based on HCM Method”, Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 945 - 958, 2005.##3. Reilly, W. R. and Gardner, C. C. (1977), “Technique for Measurement of Delay at Intersections” “, Transportation Research Record 644, TRB, National Research Council, Washington, D.C., pp. 1-7.##4. Hurdle VF, (1984) “Signalized intersection delay models – A primer for the uninitiated”, Transportation Research Record 971. pp 96-105.##5. Lin, Feng-Bor (1989), “Application of 1985 Highway Capacity Manual for Estimating Delay at Signalized Intersections”, Transportation Research Record 1225, TRB, National Research Council, Washington, D.C., pp. 18 -23.##6. Teply, S. (1989), “Accuracy of Delay Surveys at Signalized Intersections”, Transportation Research Record 1225, TRB, National Research Council, Washington, D.C., pp. 24-32.##7. Dowling, R. G. (1994), “Use of Default Parameters for Estimating Signalized Intersection Level of Service”, Transportation Research Record 1457, TRB, National Research Council, Washington, D.C., pp. 82-95.##8. Arasan, T. V. and Jagadish, K. (1995), “Effect of Heterogeneity of Traffic on Delay at Signalized Intersections”, Journal of Transportation Engineering, ASCE, Volume 121, No.4.pp. 397-404.##9. Braun, S. M. and Ivan, J. N. (1996), “Estimating Approach Delay Using 1985 and 1994 Highway Capacity Manual Procedures", Transportation Research Record 1555, TRB, National Research Council, Washington, D.C., pp. 23-32.##10. Ko J, Hunter M, and Guensler R. Measuring Control Delay Using second-by-Second GPS Speed Data”, Transportation Research Board 86th Annual meeting compendium of papers TRB 2007.##11. Maini P, Khan S. Discharge characteristics of heterogeneous traffic at signalized intersections. Proceedings of fourth International Symposium on Highway Capacity 2000; 258–270.##12. Chandra, S and Molla, D. (2010), “ Change in Vehicular Interaction and Saturation flow at Signalized Intersections over time” Highway Research journal, Indian Roads Congress, New Delhi. Volume 3. No1. Pp.69-76.##13. Chandra, S and Kumar, U. (2003) “Effect of Lane Width on Capacity under Mixed Traffic Conditions in India”, Journal of Transportation engineering ASCE, Volume 129, No.2, pp.155-160.##14. Md Hadiuzzaman, Md Mizanur Rahman and Md Ahsanul Karim. (2008), “Saturation Flow Model at Signalized Intersection for Non-lane Based Traffic” Canadian Journal of Transportation volume 2, Part 1. pp.78-90##15. Jenish Joseph and Gang-Len Chang.(2005), “ Saturation Flow Rates and Maximum Critical Lane Volumes for Planning Applications in Maryland” Journal of Transportation engineering ASCE, Volume 131, No12. pp.946-952.##16. Highway Capacity Manual. Transportation Research Board 2000.##17. Bhuyan, P.K and Krishna Rao, K.V.(2011), “Application of GPS and Clustering Techniques in defining LOS Criteria of Signalized Intersections for Indian Cities” Highway Research journal, Indian Roads Congress, New Delhi. Volume 4. No1. Pp.69-75.##18. Aloysius Tjan and Ria Sujoto (2008), “Verification of HCM 2000 Delay Equation on a Ideal Signalized Junction in Bandung” (Junction of Asia Afrika And Tamblong) Proceedings of the Eastern Asia Society for Transportation Studies, Vol.4, October, 2003.pp583-595.## ##

A mathematical model for determination of structural value of geotextile in pavements 2 2 The use of geotextiles to postpone reflective cracks in asphalt overlay is a popular practice, so researchers are eager to calculate its structural value. This research study has focused on this issue for geotextiles used in the roads of Iran. Twelve sections from the Tehran-Qom road were tested each examined before and after construction of the overlay. The tests were of the Falling Weight Deflectometer type, and at least twelve tests were conducted each time. The data from five sections (four for developing the model and one for evaluating the output) allowed a new mathematical model to be developed. For the seven remaining sections, some foreign and Iranian geotextiles were used as interlayers. The mean structural value for all of the geotextiles was equivalent to that of a 2.92 cm-thick Hot Mix Asphalt overlay, while that for only the Iranian sections was equivalent to 2.28 cm. Economic evaluations, based on construction costs, showed that in 2011 the use of geotextiles was economical in Iran, because fuel and bitumen subsidies had been eliminated and different geotextile brands had been brought to market in the country. 60 66 2012/04/102011/11/162011/02/102010/08/302010/04/242011/08/312011/10/25 1390/8/3 2013/03/162013/04/102013/03/162013/03/162013/03/172013/03/162013/04/10 1392/1/21 M. Ameri M. Ameri Iran University of Science and Technology Iran Ameri@iust.ac.ir J. Shahi J. Shahi Iran University of Science and Technology Iran jalil@iust.ac.ir H. Khani sanij H. Khani sanij Iran University of Science and Technology Iran khani@iust.ac.ir Structural value Geosynthetics Geotextile Falling Weight deflectometer Non-destructive test Hot mix asphalt [1] Button, J.W. and Lytton, R.L.: 2007, Guidelines for Using Geosynthetics with Hot Mix Asphalt Overlays to Reduce Reflective Cracking, In Transportation Research Board 2007 Annual Meeting CD-ROM, Transportation Research Board of the National Academies, Washington D,C.## [2] Khodaii, A. and Fallah, Sh.: 2009, Effects of Geosynthetic Reinforcement on the Propagation of##Reflection Cracking in Asphalt Overlays, International Journal of Civil Engineering. Vol. 7, No. 2, pp. 131-140.##[3] Moghaddas Tafreshi, S.N. and Asakereh, A.: 2007, Strength evaluation of wet reinforced silty sand by triaxial test, International Journal of Civil Engineering. Vol. 5, No. 4, pp. 274-283.##[4] Barnhart, V.T.: 1989, Field Evaluation of Experimental Fabrics to Prevent Reflective Cracking in Bituminous Resurfacing, Report No. R-1300, Materials & Technology Division, Michigan Transportation Commission. Lansing, Michigan.##[5] Naeini, S. A. and Ziaie Moayed. R.: 2009, Effect of Plasticity Index and Reinforcement on the CBR Value of Soft Clay, International Journal of Civil Engineering. Vol. 7, No. 2, pp. 124-130.##[6] Pak, A. and Zahmatkesh, Z.: 2011, Experimental study of geotextile\'s drainage and filteration propertis under different hydraulic gradients and confining pressures, International Journal of Civil Engineering. Vol. 9, No. 2, pp. 97-102.##[7] Holtz, R.D. Christopher, B.R. and Berg, R.R.: 1998, Geosynthetic Design and Construction Guidelines, Publication No. FHWA HI-95-038, NHI Course No. 13213, National Highway Institute, Federal Highway Administration, U.S. Department of Transportation.##[8] Predoehl, N.H.: 1990, Evaluation of Paving Fabric Test Installations in California, Report No. FHWA/CA/TL-90/02. California Department of Transportation, Sacramento, California.##[9] Carmichael, R.F. and Marienfeld, M.L.: 1999, Synthesis and Literature Review of Nonwoven Paving Fabrics Performance in Overlays, In Transportation Research Record No. 1687, Geotechnical Aspects of Pavements, TRB National Research Council, Washington, D.C., pp 112-124.##[10] Sprague, C.J.: 2006, Study of the Cost-Effectiveness of Various Flexible Pavement Maintenance Treatments, In Transportation Research Circular Maintenance Management 2008. Presentations from the 11th AASHTO-TRB Maintenance Management Conference, Number E-C098.TRB, National Research Council, Washington D.C, pp 45-53.##[11] Young, S.D. Sung, H.B. and Kwang, W.K.: 2009, Estimation of relative performance of reinforced overlaid asphalt concretes against reflection cracking due to bending more fracture, Construction and Building Materials, Volume 23, Issue 5, Pages 1803-1807.##[12] ASTM.: 2010, Standard Test Method for Deflections with a Falling-Weight-Type Impulse Load Device, ASTM D4694 – 09, Volume 04.03.##[13] AASHTO.: 1993, AASHTO Guide for Design of Pavement Structures, AASHTO, Washington D.C., USA.## ##