The multi-wave algorithm (Glover, 2016) integrates tabu search and strategic oscillation utilizing repeated waves (nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem (UFLP) to minimize the combined costs of selecting facilities to be opened and of assigning each customer to an opened facility in order to meet the customers' demands. The objective is to minimize the overall cost including the costs of opening facilities and the costs of allocations. Our experimental tests on a standard set of benchmarks for this widely-studied class of problems show that our algorithm outperforms all previous methods.
Abstract:In this paper, we treat the capacitated location-routing problem (CLRP). The CLRP which combines the facility location problem with the routing problem is one of the most important problems in combinatorial optimisation field. In this study, we propose a new two-stage heuristic (2-SH) algorithm for the large-scale CLRP. In fact, our aim is to find high-quality solutions for very large-scale problems within a short computing time. The proposed method consists of two major stages. In the first, the routing sub-problem is solved using a tabu search. Then, in the second stage, to associate each route to a facility, the location-allocation sub-problem is treated by means of a simulated annealing method. Our proposed approach is evaluated on large-scale randomly generated instances and compared successfully with other two state-of-the-art algorithms from the literature.
The dial-a-ride problem (DARP), is a variant of the pickup and delivery problem (PDP), consists of designing vehicle routes of n customers transportation requests. The problem arises in many transportation applications, like door-to-door transportation services for elderly and disabled people or in services for patients. This paper consider a static multivehicle DARP, which the objective is to minimize a combined costs of total travel distance, total duration, passengers waiting time, the excess ride time of customers, and the early arrival time while respecting maximum route duration limit, the maximum costumer ride time limit, the capacity and the time window constraint. The authors propose a two-phase scheduling method combined to the tabu search heuristic, for the static multivehicle DARP. Their experimentation report best results for Cordeau Benchmark test problem, compared to reported results.
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