A Recourse Stochastic Goal Programming Approach for the Multi-objective Stochastic Vehicle Routing Problem

This paper addresses a multi‐objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles in use and the probability of an accident are simultaneously minimized. We suppose that demands and travel durations are of a stochastic natu...

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Vydané v:Journal of multi-criteria decision analysis Ročník 23; číslo 1-2; s. 3 - 14
Hlavní autori: Masri, Hatem, Ben Abdelaziz, Fouad, Alaya, Houda
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Chichester Blackwell Publishing Ltd 01.01.2016
Wiley Periodicals Inc
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ISSN:1057-9214, 1099-1360
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Abstract This paper addresses a multi‐objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles in use and the probability of an accident are simultaneously minimized. We suppose that demands and travel durations are of a stochastic nature. In order to build a certainty equivalent program to the multi‐objective stochastic vehicle routing problem, we propose a solution strategy based on a recourse approach, a chance‐constrained approach and a goal‐programming approach. The resulting certainty equivalent program is solved to optimality using CPLEX. Copyright © 2016 John Wiley & Sons, Ltd.
AbstractList This paper addresses a multi-objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles in use and the probability of an accident are simultaneously minimized. We suppose that demands and travel durations are of a stochastic nature. In order to build a certainty equivalent program to the multi-objective stochastic vehicle routing problem, we propose a solution strategy based on a recourse approach, a chance-constrained approach and a goal-programming approach. The resulting certainty equivalent program is solved to optimality using CPLEX.
This paper addresses a multi‐objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles in use and the probability of an accident are simultaneously minimized. We suppose that demands and travel durations are of a stochastic nature. In order to build a certainty equivalent program to the multi‐objective stochastic vehicle routing problem, we propose a solution strategy based on a recourse approach, a chance‐constrained approach and a goal‐programming approach. The resulting certainty equivalent program is solved to optimality using CPLEX. Copyright © 2016 John Wiley & Sons, Ltd.
Author Alaya, Houda
Masri, Hatem
Ben Abdelaziz, Fouad
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  givenname: Hatem
  surname: Masri
  fullname: Masri, Hatem
  email: Correspondence to: College of Business Administration, University of Bahrain, PO Box 32038, Sakhir, Bahrain. , hmasri@uob.edu.bh
  organization: College of Business Administration, University of Bahrain, Sakhir, Bahrain
– sequence: 2
  givenname: Fouad
  surname: Ben Abdelaziz
  fullname: Ben Abdelaziz, Fouad
  organization: NEOMA Business School, Mont-Saint-Aignan, France
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  givenname: Houda
  surname: Alaya
  fullname: Alaya, Houda
  organization: Institut Supérieur de Gestion, University of Tunis, Le Bardo, Tunisia
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References Ben Abdelaziz F, Masri H. 2010. A compromise solution for the multiobjective stochastic linear programming under partial uncertainty. European Journal of Operational Research 202(1): 55-59.
Ghoseiri K, Ghannadopour SF. 2010. Multi-objective vehicle routing problem with time windows using goal programming and genetic algorithm. Applied Soft Computing 10: 1096-1107.
Fölsz F, Mészáros C, Rapcsák T. 1995. Distribution of gas cylinders. European Journal of Operational Research 87(3): 613-623.
Zhao Y, Li C, Zhang J, Ren X, Ren W. 2011. Research on vehicle routing problem with stochastic demand based on multi-objective methodICIC 1. Lecture Notes in Computer Science 6838: 153-161, Springer.
Laporte G, Louveaux FV. 1993. The integer L-shaped method for stochastic integer programs with complete recourse. Operations Research Letters 13: 133-142.
Laporte G, Louveaux FV, Van Hamme L. 1994. Exact solution of a stochastic location problem by an integer L-shaped algorithm. Transportation Science 28: 95-103.
Laporte G, Louveaux F, Mercure H. 1989. Models and exact solutions for a class of stochastic location-routing problems. European Journal of Operational Research 39(1): 71-78.
Tan KC, Cheong CY, Goh CK. 2007. Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation. European Journal of Operational Research 117: 813-839.
Walkup DW, Wets RJ-B. 1967. Stochastic programs with recourse. SIAM Journal on Applied Mathematics 15(5): 1299-1314.
Laporte G, Louveaux FV, Mercure H. 1992. The vehicle routing problem with stochastic travel times. Transportation Science 26: 161-170.
Bertsimas DJ. 1992. A vehicle routing problem with stochastic demand. Operations Research 40: 574-585.
Ben Abdelaziz F. 2012. Solution approaches for the multiobjective stochastic programming. European Journal of Operational Research 216(1): 1-16.
Ben Abdelaziz F, Aouni B, El Fayedh R. 2007. Multi-objective stochastic programming for portfolio selection. European Journal of Operational Research 177: 1811-1823.
Mendoza JE, Villegas JG. 2013. A multi-space sampling heuristic for the vehicle routing problem with stochastic demands. Optimization Letters 7(7): 1503-1516.
Thompson P, Psaraftis H. 1993. Cyclic transfer algorithms for multi-vehicle routing and scheduling problems. Operations Research 41(5): 935-946.
Gendreau M, Laporte G, Seguin R. 1995. An exact algorithm for the vehicle routing problem with stochastic demands and customers. Transportation Science 29(2): 143-155.
Jozefowiez N, Semet F, Talbi E-G. 2008. Multi-objective vehicle routing problems. European Journal of Operational Research 189(2): 293-309.
Aouni B, Ben Abdelaziz F, La Torre D. 2012. The stochastic goal programming model: theory and applications. Journal of Multi-Criteria Decision Analysis 19(5-6): 185-200.
Stewart WR, Golden BL. 1983. Stochastic vehicle routing: a comprehensive approach. European Journal of Operational Research 14: 371-385.
Gass S, Saaty T. 1955. The computational algorithm for the parametric objective function. Naval Research Logistics Quarterly 2: 39-45.
Lambert V, Laporte G, Louveaux F. 1993. Designing collection routes through bank branches. Computers & Operations Research 20(7): 783-791.
Park YB, Koelling CP. 1986. A solution of vehicle routing problems in a multiple objective environment. Engineering Costs and Production Economics 10: 121-32.
Calavete HI, Galé C, Oliveros M, Sànchez-Valverde B. 2007. A goal programming approach to vehicle routing problems with soft time windows. European Journal of Operational Research 177: 1720-1733.
Christiansen C, Lysgaard J. 2007. A branch-and-price algorithm for the capacitated vehicle routing problem with stochastic demands. Operations Research Letters 35(6): 773-781.
Goodson JC, Ohlmann JW, Thomas BW. 2012. Cyclic-order neighborhoods with application to the vehicle routing problem with stochastic demand. European Journal of Operational Research 227(2): 312-323.
Masmoudi M, Ben Abdelaziz F. 2012. A recourse goal programming approach for the portfolio selection problem. INFOR: Information Systems and Operational Research 50(3): 134-139.
Miller C, Tucker A, Zemlin RA. 1960. Integer programming formulation of traveling salesman problems. ACM 7(4): 326-329.
Ando N, Taniguchi E. 2006. Travel time reliability in vehicle routing and scheduling with time windows. Networks and Spatial Economics 6: 293-311.
Guitouni A, Masri H. 2014. An orienteering model for the search and rescue problem. Computational Management Science 11(4): 459-473.
Charnes A, Cooper WW. 1971. Chance-constrained programming. Management Science 5: 73-79.
Tas D, Dellaert N, van Woensel T, de Kok T. 2013. Vehicle routing problem with stochastic travel times including soft time windows and service costs. Computers and Operations Research 40(1): 214-224.
Li X, Tian P, Leung SC. 2010. Vehicle routing problems with time windows and stochastic travel and service times: models and algorithm. International Journal of Production Economics 125: 137-145.
2010; 10
1986; 10
2010; 202
2010; 125
2013; 40
1993; 20
1993; 41
2012; 19
2006; 6
1960; 7
1994; 28
2008; 189
2013; 7
2015; 8
2012; 227
2007; 35
1955; 2
1983; 14
2012; 50
1993; 13
2007; 117
2011; 6838
2007; 177
1995; 87
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2012; 216
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1989; 39
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– reference: Ben Abdelaziz F, Aouni B, El Fayedh R. 2007. Multi-objective stochastic programming for portfolio selection. European Journal of Operational Research 177: 1811-1823.
– reference: Stewart WR, Golden BL. 1983. Stochastic vehicle routing: a comprehensive approach. European Journal of Operational Research 14: 371-385.
– reference: Ben Abdelaziz F, Masri H. 2010. A compromise solution for the multiobjective stochastic linear programming under partial uncertainty. European Journal of Operational Research 202(1): 55-59.
– reference: Ando N, Taniguchi E. 2006. Travel time reliability in vehicle routing and scheduling with time windows. Networks and Spatial Economics 6: 293-311.
– reference: Guitouni A, Masri H. 2014. An orienteering model for the search and rescue problem. Computational Management Science 11(4): 459-473.
– reference: Goodson JC, Ohlmann JW, Thomas BW. 2012. Cyclic-order neighborhoods with application to the vehicle routing problem with stochastic demand. European Journal of Operational Research 227(2): 312-323.
– reference: Laporte G, Louveaux FV, Van Hamme L. 1994. Exact solution of a stochastic location problem by an integer L-shaped algorithm. Transportation Science 28: 95-103.
– reference: Mendoza JE, Villegas JG. 2013. A multi-space sampling heuristic for the vehicle routing problem with stochastic demands. Optimization Letters 7(7): 1503-1516.
– reference: Walkup DW, Wets RJ-B. 1967. Stochastic programs with recourse. SIAM Journal on Applied Mathematics 15(5): 1299-1314.
– reference: Charnes A, Cooper WW. 1971. Chance-constrained programming. Management Science 5: 73-79.
– reference: Thompson P, Psaraftis H. 1993. Cyclic transfer algorithms for multi-vehicle routing and scheduling problems. Operations Research 41(5): 935-946.
– reference: Tas D, Dellaert N, van Woensel T, de Kok T. 2013. Vehicle routing problem with stochastic travel times including soft time windows and service costs. Computers and Operations Research 40(1): 214-224.
– reference: Calavete HI, Galé C, Oliveros M, Sànchez-Valverde B. 2007. A goal programming approach to vehicle routing problems with soft time windows. European Journal of Operational Research 177: 1720-1733.
– reference: Laporte G, Louveaux FV. 1993. The integer L-shaped method for stochastic integer programs with complete recourse. Operations Research Letters 13: 133-142.
– reference: Laporte G, Louveaux FV, Mercure H. 1992. The vehicle routing problem with stochastic travel times. Transportation Science 26: 161-170.
– reference: Masmoudi M, Ben Abdelaziz F. 2012. A recourse goal programming approach for the portfolio selection problem. INFOR: Information Systems and Operational Research 50(3): 134-139.
– reference: Zhao Y, Li C, Zhang J, Ren X, Ren W. 2011. Research on vehicle routing problem with stochastic demand based on multi-objective methodICIC 1. Lecture Notes in Computer Science 6838: 153-161, Springer.
– reference: Park YB, Koelling CP. 1986. A solution of vehicle routing problems in a multiple objective environment. Engineering Costs and Production Economics 10: 121-32.
– reference: Ben Abdelaziz F. 2012. Solution approaches for the multiobjective stochastic programming. European Journal of Operational Research 216(1): 1-16.
– reference: Ghoseiri K, Ghannadopour SF. 2010. Multi-objective vehicle routing problem with time windows using goal programming and genetic algorithm. Applied Soft Computing 10: 1096-1107.
– reference: Christiansen C, Lysgaard J. 2007. A branch-and-price algorithm for the capacitated vehicle routing problem with stochastic demands. Operations Research Letters 35(6): 773-781.
– reference: Lambert V, Laporte G, Louveaux F. 1993. Designing collection routes through bank branches. Computers & Operations Research 20(7): 783-791.
– reference: Gendreau M, Laporte G, Seguin R. 1995. An exact algorithm for the vehicle routing problem with stochastic demands and customers. Transportation Science 29(2): 143-155.
– reference: Fölsz F, Mészáros C, Rapcsák T. 1995. Distribution of gas cylinders. European Journal of Operational Research 87(3): 613-623.
– reference: Miller C, Tucker A, Zemlin RA. 1960. Integer programming formulation of traveling salesman problems. ACM 7(4): 326-329.
– reference: Bertsimas DJ. 1992. A vehicle routing problem with stochastic demand. Operations Research 40: 574-585.
– reference: Tan KC, Cheong CY, Goh CK. 2007. Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation. European Journal of Operational Research 117: 813-839.
– reference: Li X, Tian P, Leung SC. 2010. Vehicle routing problems with time windows and stochastic travel and service times: models and algorithm. International Journal of Production Economics 125: 137-145.
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Snippet This paper addresses a multi‐objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles...
This paper addresses a multi-objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles...
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SubjectTerms Goal programming
multi-objective programming
Route choice
Stochastic models
stochastic programming
Studies
Transportation problem (Operations research)
vehicle routing problem
Vehicles
Title A Recourse Stochastic Goal Programming Approach for the Multi-objective Stochastic Vehicle Routing Problem
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