Abstract
Orienteering problem is a well researched routing problem which is a generalization of the traveling salesman problem. Team orienteering problem (TOP) is the extended version of the orienteering problem with more than one member in the team. In this paper the first known discrete particle swarm optimization (DPSO) algorithm has been developed for 2, 3 and 4-member TOP. In the DPSO meta-heuristic novel methods have been introduced for the initial particle generation process. Reduced variable neighborhood search and 2-opt were applied as the local search tools. The efficacy of the algorithm was tested using seven commonly used benchmark problem sets ranging in size from 21 to 102 nodes. The results of the DPSO algorithm were compared against seven other heuristic algorithms that have been developed for TOP. It was concluded that the developed DPSO algorithm for the TOP is competitive and robust across the benchmark problem sets.
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References
Anghinolfi D, Paolucci M (2009) A new discrete particle swarm optimization approach for the single-machine total weighted tardiness scheduling problem with sequence-dependent setup times. Eur J Oper Res 193(1): 73–85
Archetti C, Hertz A, Speranza MG (2007) Metaheuristics for the team orienteering problem. J Heuristics 13: 49–76
Bouly H, Dang D, Moukrim A (2010) A memetic algorithm for the team orienteering problem. 4OR 8(1): 49–70
Boussier S, Feillet D, Gendreau M (2007) An exact algorithm for team orienteering problems. 4OR 5: 211–230
Butt SE, Cavalier TM (1994) A heuristic for the multiple tour maximum collection problem. Comput Oper Res 21(1): 101–111
Butt S, Ryan D (1999) An optimal solution procedure for the multiple path maximum collection problem using column generation. Comput Oper Res 26: 427–441
Chao IM, Golden BL, Wasil EA (1996) The team orienteering problem. Eur J Oper Res 88: 464–474
Dallard H, Lam S, Kulturel-Konak S (2006) A particle swarm optimization approach to the orienteering problem. In: Proc Ind Eng Res Conf Orlando, FL
Dallard H, Lam S, Kulturel-Konak S (2007) Solving the orienteering problem using attractive and repulsive particle swarm optimization. In: Int Conf Inf Reuse Integration Las Vegas, NV
Golden BL, Levy L, Vohra R (1987) The orienteering problem. Navig Res Log 34: 307–318
Golden BL, Wang Q, Liu L (1988) A multifaceted heuristic for the orienteering problem. Navig Res Log 354: 359–366
Hermann B, Duc-Cuong D, Aziz M (2010) A memetic algorithm for the team orienteering problem. 4OR Q J Oper Res 8(1): 49–70
Jarboui B, Cheikh M, Siarry P, Rebai A (2007) Combinatorial particle swarm optimization (CPSO) for partitional clustering problem. Appl Math Comp 192: 337–345
Jarboui B, Damak N, Siarry P, Rebai A (2008) A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Appl Math Comp 195: 299–308
Jarboui B, Ibrahim S, Siarry P, Rebai A (2008) A combinatorial particle swarm optimization for solving permutation flowshop problems. Comput Ind Eng 54: 526–538
Jin YX, Cheng HZ, Yan JY, Zhang L (2007) New discrete method for particle swarm optimization and its application in transmission network expansion planning. Electr Power Syst Res 77: 227–233
Ke L, Archetti C, Feng Z (2008) Ants can solve the team orienteering problem. Comput Ind Eng 54(3): 648–665
Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proc IEEE Intl Conf Neur Net, pp 1942–1948
Lian A, Jiao B, Gu X (2006) A similar particle swarm optimization algorithm for job-shop scheduling to minimize makespan. Appl Math Comp 183: 1008–1017
Lian Z, Gu X, Jia B (2008) A novel particle swarm optimization algorithm for permutation flow-shop scheduling to minimize makespan. Chaos Solitons Fractals 35: 851–861
Pan QK, Tasgetiren MF, Liang YC (2008) A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem. Comput Oper Res 35: 2807–2839
Pang W, Wang KP, Zhou CG, Dong LJ (2004) Fuzzy discrete particle swarm optimization for solving traveling salesman problem. In: Proc Fourth Intl Conf Comp Info Tech, pp 796–800
Sevkli Z, Sevilgen FE (2006) Variable neighborhood search for the orienteering problem. In: Proc Intl Symp Comp Info Sci Istanbul, Turkey
Sevkli Z, Sevilgen FE, Keles O (2007) Particle swarm optimization for the orienteering problem. In: Int Symp Innov Intel Sys App Istanbul, Turkey
Shi Y, Eberhart RC (1999) Empirical study of particle swarm optimization. In: Proc Cong Evol Comp, pp 1945–1950
Souffriau W, Vansteenwegen P, Berghe GV, Van OD (2010) A path relinking approach for the team orienteering problem. Comput Oper Res 37(11): 1853–1859
Tang H, Miller-Hooks E (2005) A TABU search heuristic for the team orienteering problem. Comput Oper Res 32: 1379–1407
Tasgetiren MF, Liang YC, Sevkli M, Gencyilmaz G (2007) A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem. Eur J Oper Res 177: 930–947
Tseng CT, Liao CJ (2008) A discrete particle swarm optimization for lot-streaming flowshop scheduling problem. Eur J Oper Res 191(2): 360–373
Tsiligirides T (1984) Heuristic methods applied to orienteering. J Oper Res Soc 35(9): 797–809
Vansteenwegen P, Souffriau W, Berghe GV, Oudheusden DV (2009) A guided local search metaheuristic for the team orienteering problem. Eur J Oper Res 196(1): 118–127
Venter G, Sobieski J (2002) Particle swarm optimization. 43rd AIAA/ASME/ASCE/AHS/ASC Struc, Struct Dyn, Mtl Conf Denver, CO
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Muthuswamy, S., Lam, S.S. Discrete particle swarm optimization for the team orienteering problem. Memetic Comp. 3, 287–303 (2011). https://doi.org/10.1007/s12293-011-0071-x
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DOI: https://doi.org/10.1007/s12293-011-0071-x