A Path Relinking Algorithm for the Generalized Assignment Problem

Multiobjective Landscape Analysis and the Generalized Assignment Problem

“…Thus, for large instances, heuristic and metaheuristic methods have received a great deal of attention, including tabu search approaches [11,12], variable depth search [13,14], ant colony optimization [15], evolutionary algorithms [16], and more recently, path relinking algorithms [17,18,19,20].…”

Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem

“…Chu and Beasley (1997) presented a Genetic Algorithm for GAP that tries to improve feasibility and optimality simultaneously. Different variable depth search algorithms (Racer and Amini (1994), Yagiura et al (1998Yagiura et al ( , 1999), Ejection Chain based Tabu Search algorithms (Laguna et al (1995), Diaz and Fernandez (2001), Yagiura et al (2004)), Path Relinking approaches (Alfandari et al (2001(Alfandari et al ( , 2002(Alfandari et al ( , 2004, Yagiura et al (2001Yagiura et al ( , 2002Yagiura et al ( , 2006) , Ant Colony Optimization (Randall (2004)), Max-Min Ant System Heuristic based on greedy randomized adaptive heuristic (Lourencp and Serra (2002)) can be mentioned as the other meta-heuristic approaches proposed for GAP in recent years. The aim of this study is to present an artificial bee colony algorithm to solve GAP.…”

A path relinking approach with ejection chains for the generalized assignment problem

“…To the best of our knowledge, our paper [32] (a preliminary extended abstract of this paper) was the first paper that reported computational results of a path relinking approach for the GAP, in which results for benchmark instances with up to 200 jobs were reported. Alfandari et al [1] independently proposed another effective path relinking algorithm slightly earlier, although without reporting any computational results in the original version of their paper. (The full version [2] containing computational results appeared somewhat later, and we compare their method with ours in Section 4.)…”

“…Alfandari et al [1] independently proposed another effective path relinking algorithm slightly earlier, although without reporting any computational results in the original version of their paper. (The full version [2] containing computational results appeared somewhat later, and we compare their method with ours in Section 4.) Our algorithm also features an ejection chain approach, likewise associated with tabu search [11,33], where Lagrangian relaxation provides adjusted cost information to guide the neighborhood search to promising solutions.…”

“…Computational comparisons are conducted on benchmark GAP instances known as types B, C, D and E. These test problems are taken from the OR-Library, 1 which is the primary repository for such problems, and are supplemented by additional test instances generated by ourselves. The proposed algorithm is compared with many existing heuristic algorithms including the recent path relinking approach by Alfandari et al [2,3], tabu search by Díaz and Fernández [6], a Lagrangian heuristic algorithm by Haddadi and Ouzia [14], tabu search by Yagiura et al [33], variable depth search algorithms by Yagiura et al [34,35], another variable depth search algorithm by Racer and Amini [26], tabu search by Laguna et al [18], MAX-MIN ant system by Lourenço and Serra [20], genetic algorithm by Chu and Beasley [4] and a mixed integer programming solver CPLEX 6.5.…”