Active-guided evolution strategies for large-scale capacitated vehicle routing problems

Enhanced mixed integer programming techniques and routing problems

“…On the CMT instances, the best solutions are obtained by Taillard [161] in 12 cases out of 14, Rochat and Taillard [151] for all the instances but E200-17c, Mester and Bräysy [125] for all the instances but D200-18c. On the GWKC instances, the best solutions are obtained by Mester and Bräysy [125] for all the 20 instances but D281-08k, D361-09k and E400-18k, Prins [145] for instance D281-08k, Pisinger and Ropke [141] for instance D361-09k and De Franceschi et al [68] for instance E400-18k. If the two instance sets are considered together, the best performers in terms of accuracy and computing time are Mester and Bräysy [125] and Prins [145].…”

“…On the GWKC instances, the best solutions are obtained by Mester and Bräysy [125] for all the 20 instances but D281-08k, D361-09k and E400-18k, Prins [145] for instance D281-08k, Pisinger and Ropke [141] for instance D361-09k and De Franceschi et al [68] for instance E400-18k. If the two instance sets are considered together, the best performers in terms of accuracy and computing time are Mester and Bräysy [125] and Prins [145]. It should be noted that these two methods combine population search and local search approaches, thus allowing for a broad and deep exploration of the solution space.…”

“…The best solutions on the CMT instances are obtained by Gendreau et al [93], Xu and Kelly [175] and Wassan [172]. We refer the reader to [56,125,168] for a deeper analysis of the most effective heuristic and metaheuristic techniques proposed in the literature for VRP.…”

An artificial bee colony algorithm for the capacitated vehicle routing problem

“…During the past two decades, an increasing number of publications on heuristic approaches have been developed to tackle the CVRP. The work can be categorized into evolutionary algorithms (Baker and Ayechew, 2003;Berger and Barkaoui, 2003;Prins, 2004;Mester and Bräysy, 2007;Prins, 2009;Nagata and Bräysy, 2009), ant colony optimization 4…”

An improved Clarke and Wright savings algorithm for the capacitated vehicle routing problem

“…These algorithms usually find a feasible solution (near optimal) fast and easily but they do not guarantee that the optimal solution will be found. Finally, a metaheuristic algorithm, which is an iterative improvement approach by combining a heuristic algorithm with intelligent ideas for exploring and exploiting the search space, composed of simulated annealing 22 , tabu search 23,24 , genetic algorithm 25,26 , ant colony algorithm 27,28 , memetic algorithm 29,30 , active-guided evolution strategies 31 , honey bees mating optimization algorithm 32 , and particle swarm optimization algorithm 33,34 . In these algorithms, a good metaheuristic implementation can provide efficiently near-optimal solutions in a reasonable computation time.…”