This paper addresses the double vehicle routing problem with multiple stacks (DVRPMS) in which a fleet of vehicles must collect items in a pickup region and then travel to a delivery region where all items are delivered. The load compartment of all vehicles is divided into rows (horizontal stacks) of fixed profundity (horizontal heights), and on each row, the unloading process must respect the last‐in‐first‐out policy. The objective of the DVRPMS is to find optimal routes visiting all pickup and delivery points while ensuring the feasibility of the vehicle loading plans. We propose a new integer linear programming formulation, which was useful to find inconsistencies in the results of exact algorithms proposed in the literature, and a variable neighborhood search based algorithm that was able to find solutions with same or higher quality in shorter computational time for most instances when compared to the methods already present in the literature.
This paper addresses an unrelated parallel machine problem with machine and job sequence dependent setup times. The objective function considered is a linear combination of the total completion time and the total number of resources assigned. Due to the combinatorial complexity of this problem, we propose an algorithm based on the GRASP metaheuristic, in which the basic parameter that defines the restrictiveness of the candidate list during the construction phase is self-adjusted according to the quality of the solutions previously found (reactive GRASP). The algorithm uses an intensification strategy based on the path relinking technique which consists in exploring paths between elite solutions found by GRASP. The results obtained by the proposed algorithm are compared with the best results available in the literature.
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