Search results for "Guided Local Search"
showing 10 items of 16 documents
A well-scalable metaheuristic for the fleet size and mix vehicle routing problem with time windows
2009
This paper presents an efficient and well-scalable metaheuristic for fleet size and mix vehicle routing with time windows. The suggested solution method combines the strengths of well-known threshold accepting and guided local search metaheuristics to guide a set of four local search heuristics. The computational tests were done using the benchmarks of [Liu, F.-H., & Shen, S.-Y. (1999). The fleet size and mix vehicle routing problem with time windows. Journal of the Operational Research Society, 50(7), 721-732] and 600 new benchmark problems suggested in this paper. The results indicate that the suggested method is competitive and scales almost linearly up to instances with 1000 custome…
Guided local search for the optimal communication spanning tree problem
2011
This paper considers the optimal communication spanning tree (OCST) problem. Previous work analyzed features of high-quality solutions. Consequently, integrating this knowledge into a metaheuristic increases its performance for the OCST problem. In this paper, we present a guided local search (GLS) approach which dynamically changes the objective function to guide the search process into promising areas. In contrast to traditional approaches which reward promising solution features by favoring edges with low weights pointing towards the tree's center, GLS penalizes low-quality edges with large weights that do not point towards the tree's center.
The Scatter Search Methodology
2011
Scatter search (SS) is an evolutionary approach for optimization. It has been applied to problems with continuous and discrete variables and with a single or multiple objectives. The success of SS as an optimization technique is well documented in a constantly growing number of journal articles and book chapters. This article first focuses on the basic SS framework, which is responsible for most of the outcomes reported in the literature, and then covers advanced elements that have been introduced in a few selected papers, such as the hybridization with tabu search, a well-known memory-based metaheuristic. We consider the maximum diversity problem to illustrate the search elements, methods …
A powerful route minimization heuristic for the vehicle routing problem with time windows
2009
We suggest an efficient route minimization heuristic for the vehicle routing problem with time windows. The heuristic is based on the ejection pool, powerful insertion and guided local search strategies. Experimental results on the Gehring and Homberger's benchmarks demonstrate that our algorithm outperforms previous approaches and found 18 new best-known solutions.
An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
2007
In this paper, we present an efficient variable neighborhood search heuristic for the capacitated vehicle routing problem. The objective is to design least cost routes for a fleet of identically capacitated vehicles to service geographically scattered customers with known demands. The variable neighborhood search procedure is used to guide a set of standard improvement heuristics. In addition, a strategy reminiscent of the guided local search metaheuristic is used to help escape local minima. The developed solution method is specifically aimed at solving very large scale real-life vehicle routing problems. To speed up the method and cut down memory usage, new implementation concepts are use…
Active-guided evolution strategies for large-scale capacitated vehicle routing problems
2007
We present an adaptation of the active-guided evolution strategies metaheuristic for the capacitated vehicle routing problem. The capacitated vehicle routing problem is a classical problem in operations research in which a set of minimum total cost routes must be determined for a fleet of identical capacitated vehicles in order to service a number of demand or supply points. The applied metaheuristic combines the strengths of the well-known guided local search and evolution strategies metaheuristics into an iterative two-stage procedure. The computational experiments were carried out on a set of 76 benchmark problems. The results demonstrate that the suggested method is highly competitive, …
Tabu search for the Max–Mean Dispersion Problem
2015
In this paper, we address a variant of a classical optimization model in the context of maximizing the diversity of a set of elements. In particular, we propose heuristics to maximize the mean dispersion of the selected elements in a given set. This NP-hard problem was recently introduced as the maximum mean dispersion problem (MaxMeanDP), and it models several real problems, from pollution control to ranking of web pages. In this paper, we first review the previous methods for the MaxMeanDP, and then explore different tabu search approaches, and their influence on the quality of the solutions obtained. As a result, we propose a dynamic tabu search algorithm, based on three different neighb…
Tabu search and GRASP for the maximum diversity problem
2007
In this paper, we develop new heuristic procedures for the maximum diversity problem (MDP). This NP-hard problem has a significant number of practical applications such as environmental balance, telecommunication services or genetic engineering. The proposed algorithm is based on the tabu search methodology and incorporates memory structures for both construction and improvement. Although proposed in seminal tabu search papers, memory-based constructions have often been implemented in naive ways that disregard important elements of the fundamental tabu search proposals. We will compare our tabu search construction with a memory-less design and with previous algorithms recently developed for…
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…
Context-Independent Scatter and Tabu Search for Permutation Problems
2005
In this paper, we develop a general-purpose heuristic for permutations problems. The procedure is based on the scatter-search and tabu-search methodologies and treats the objective-function evaluation as a black box, making the search algorithm context-independent. Therefore, our main contribution consists of the development and testing of a procedure that uses no knowledge from the problem context to search for the optimal solution. We perform computational experiments with four well-known permutation problems to study the efficiency and effectiveness of the proposed method. These experiments include a comparison with two commercially available software packages that are also based on met…