In this paper, hybrid algorithms are developed for the multisource location-allocation problem in continuous space. Three hybrid algorithms are proposed to solve this problem that combine elements of several traditional metaheuristics (genetic algorithm and variable neighborhood search) and local searches to find near-optimal solutions. Many problems from the literature have been solved with these algorithms and the obtained results confirm the robustness of the proposed hybrid algorithms. Moreover, the results show that in comparison to the best methods in literature (GA and VNS), these algorithms provide some better solutions.
