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Search Heuristics (search + heuristic)

Distribution by Scientific Domains
Mathematics and Statistics66%

Selected Abstracts

Flexibility and complexity in periodic distribution problems

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 2 2007
Peter Francis
Abstract In this paper, we explore trade-offs between operational flexibility and operational complexity in periodic distribution problems. We consider the gains from operational flexibility in terms of vehicle routing costs and customer service benefits, as well as the costs of operational complexity in terms of modeling, solution methods, and implementation challenges for drivers and customers. The period vehicle routing problem (PVRP) is a variation of the classic vehicle routing problem in which delivery routes are constructed for a period of time; the PVRP with service choice (PVRP-SC) extends the PVRP to allow service (visit) frequency to become a decision of the model. For the periodic distribution problems represented by PVRP and PVRP-SC, we introduce operational flexibility levers and a set of quantitative measures to evaluate the trade-offs between flexibility and complexity. We develop a Tabu Search heuristic to incorporate a range of operational flexibility options. We analyze the potential value and the increased operational complexity of the flexibility levers. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007 [source]

Social Infrastructure Planning: A Location Model and Solution Methods

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 8 2007
Joćo F. Bigotte
Authorities want to determine where to locate the facilities of a social infrastructure network and what should be the capacity of these facilities. Each user must be assigned to its closest facility and, to be economically viable, each facility must serve at least a pre-specified level of demand. The objective is to maximize the accessibility to facilities (i.e., to minimize the distance traveled by users to reach the facilities). A location model that captures the above features is formulated and different solution methods are tested. Among the methods tested, tabu search and a specialized local search heuristic provided the best solutions. The application of the model is illustrated through a case study involving the location of preschools in the municipality of Miranda do Corvo, Portugal. [source]

A branch-and-cut algorithm for partition coloring

NETWORKS: AN INTERNATIONAL JOURNAL, Issue 3 2010
Yuri Frota
Abstract Let G = (V, E, Q) be a undirected graph, where V is the set of vertices, E is the set of edges, and Q = {Q1,,,Qq} is a partition of V into q subsets. We refer to Q1,,,Qq as the components of the partition. The partition coloring problem (PCP) consists of finding a subset V, of V with exactly one vertex from each component Q1,,,Qq and such that the chromatic number of the graph induced in G by V, is minimum. This problem is a generalization of the graph coloring problem. This work presents a branch-and-cut algorithm proposed for PCP. An integer programing formulation and valid inequalities are proposed. A tabu search heuristic is used for providing primal bounds. Computational experiments are reported for random graphs and for PCP instances originating from the problem of routing and wavelength assignment in all-optical WDM networks. © 2009 Wiley Periodicals, Inc. NETWORKS, 2010 [source]

Classical and modern heuristics for the vehicle routing problem

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 4-5 2000
G. Laporte
Abstract This article is a survey of heuristics for the Vehicle Routing Problem. It is divided into two parts: classical and modern heuristics. The first part contains well-known schemes such as, the savings method, the sweep algorithm and various two-phase approaches. The second part is devoted to tabu search heuristics which have proved to be the most successful metaheuristic approach. Comparative computational results are presented. [source]

Neighborhood search heuristics for selecting hierarchically well-formulated subsets in polynomial regression

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 1 2010
Michael J. Brusco
Abstract The importance of subset selection in multiple regression has been recognized for more than 40 years and, not surprisingly, a variety of exact and heuristic procedures have been proposed for choosing subsets of variables. In the case of polynomial regression, the subset selection problem is complicated by two issues: (1) the substantial growth in the number of candidate predictors, and (2) the desire to obtain hierarchically well-formulated subsets that facilitate proper interpretation of the regression parameter estimates. The first of these issues creates the need for heuristic methods that can provide solutions in reasonable computation time; whereas the second requires innovative neighborhood search approaches that accommodate the hierarchical constraints. We developed tabu search and variable neighborhood search heuristics for subset selection in polynomial regression. These heuristics are applied to a classic data set from the literature and, subsequently, evaluated in a simulation study using synthetic data sets. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010 [source]