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Efficient Swarm Algorithms to Constrained Resource Allocation

Authors:
Peng-Yeng Yin
Jing-Yu Wang

Keywords: particle swarm optimization; ant colony optimization; metaheuristic; resource allocation

Abstract:
Resource management is the effective deployment for an organization’s resources. It deals with classification, allocation, stocking, processing, storage, and valuation for the shared resources when they are needed. Among many managerial tasks, the constrained resource allocation problem has challenging many practitioners involved in manufacturing operations. This problem seeks to find an optimal allocation of a limited amount of resource to a number of manufacturing activities for optimizing organization’s objective subject to the resource constraints. Most existing methods use mathematical programming techniques, but they are defaced in deriving exact solutions for large-scale problems with reasonable time. A viable alternative is to use swam algorithms which can obtain approximate solutions to real-world intractable problems. This paper presents two swarm algorithms embodying the adaptive resource bound technique for conquering the constrained nonlinear resource allocation problem. Experimental results manifest that the proposed methods are more effective and efficient than a genetic algorithm-based approach. The convergence behavior of the proposed methods is analyzed by observing the variations of population entropy. Finally, a worst-case analysis is conducted to provide a reliable performance guarantee.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2011

Publication date: September 25, 2011

Published in: conference

ISSN: 2308-3735

ISBN: 978-1-61208-154-0

Location: Rome, Italy

Dates: from September 25, 2011 to September 30, 2011