Search results for "Parallel metaheuristic"
showing 5 items of 5 documents
A Simple Metaheuristic for the FleetSize and Mix Problem with TimeWindows
2017
This paper presents a powerful new single-parameter metaheuristic to solve the Fleet Size and Mix Vehicle Routing Problem with Time Windows. The key idea of the new metaheuristic is to perform a random number of random-sized jumps in random order through four well-known local search operators. Computational testing on the 600 large-scale benchmarks of Bräysy et al. (Expert Syst Appl 36(4):8460–8475, 2009) show that the new metaheuristic outperforms previous best approaches, finding 533 new best-known solutions. Despite the significant number of random components, it is demonstrated that the variance of the results is rather low. Moreover, the suggested metaheuristic is shown to scale almost…
Towards Multilevel Ant Colony Optimisation for the Euclidean Symmetric Traveling Salesman Problem
2015
Ant Colony Optimization ACO metaheuristic is one of the best known examples of swarm intelligence systems in which researchers study the foraging behavior of bees, ants and other social insects in order to solve combinatorial optimization problems. In this paper, a multilevel Ant Colony Optimization MLV-ACO for solving the traveling salesman problem is proposed, by using a multilevel process operating in a coarse-to-fine strategy. This strategy involves recursive coarsening to create a hierarchy of increasingly smaller and coarser versions of the original problem. The heart of the approach is grouping the variables that are part of the problem into clusters, which is repeated until the size…
An ILS-Based Metaheuristic for the Stacker Crane Problem
2012
[EN] In this paper we propose a metaheuristic algorithm for the Stacker Crane Problem. This is an NP-hard arc routing problem whose name derives from the practical problem of operating a crane. Here we present a formulation and a lower bound for this problem and propose a metaheuristic algorithm based on the combination of a Multi-start and an Iterated Local Search procedures. Computational results on a large set of instances are presented.
Strategies for accelerating ant colony optimization algorithms on graphical processing units
2007
Ant colony optimization (ACO) is being used to solve many combinatorial problems. However, existing implementations fail to solve large instances of problems effectively. In this paper we propose two ACO implementations that use graphical processing units to support the needed computation. We also provide experimental results by solving several instances of the well-known orienteering problem to show their features, emphasizing the good properties that make these implementations extremely competitive versus parallel approaches.
General Concepts in Metaheuristic Search
2017
Metaheuristics have become a very popular family of solution methods for optimization problems because they are capable of finding “acceptable” solutions in a “reasonable” amount of time. Most optimization problems in practice are too complex to be approached by exact methods that can guarantee finding global optimal solutions. The time required to find and verify globally optimal solutions is impractical in most applications. An entire computational theory, which we will not discussed here, has been developed around problem complexity. It suffices to say that it is now known that the great majority of the optimization problems found in practice fall within a category that makes them “compu…