Vehicle routing problems have been extensively studied using a variety of search methods and meta-heuristics. However, most search methods are carried out using only a single improvement heuristic. Here, we report on a study using four improvement heuristics embedded in a simple steepest descent search engine. We conclude that reasonable results can be produced quickly by this simple method. A ...

Quadratic assignment problem (QAP) is a well-known problem in the facility location and layout. It belongs to the NP-complete class. There are many heuristic and meta-heuristic methods, which are presented for QAP in the literature. In this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and VNZ as heuristic methods and tabu search (TS), simulated annealing, and pa...

Large-scale unconditional and conditional vertex p-centre problems are solved using two meta-heuristics. One is based on a three-stage approach whereas the other relies on a guided multi-start principle. Both methods incorporate Variable Neighbourhood Search, exact method, and aggregation techniques. The methods are assessed on the TSP dataset which consist of up to 71,009 demand points with p ...

Techniques that combine myopic problem specific methods and a meta-strategy, which guides the search out of local optimum, are currently providing the best results. Such hybrid methods are known as iterated local search algorithms or meta-heuristics. Despite the good results achieved by these methods the inability of many current meta-heuristics to provide a wide exploration of the search space...

Meta-heuristics are commonly applied to solve various global optimization problems. In order make the meta-heuristics performing a search, balancing their exploration and ability is still an open avenue. This manuscript proposes novel Opposition-based learning scheme, called “PCOBL” (Partial Centroid Learning), inspired by partial centroid. PCOBL aims improve performance through maintaining eff...

The Two-Echelon Vehicle Routing Problem (2E-VRP) is an extension of the classical VRP where the delivery from a single depot to customers is managed by routing and consolidating the freight through intermediate depots called satellites. We presented several meta-heuristics based on separating the first and second level routing problems and solving iteratively the two resulting routing subproble...

Abstract Variational quantum algorithms, a class of heuristics, are promising candidates for the demonstration useful computation. Finding best way to amplify performance these methods on hardware is an important task. Here, we evaluate optimization heuristics with existing techniques called “meta-learners.” We compare meta-learner evolutionary strategies, L-BFGS-B and Nelder-Mead approaches, t...