DocumentCode :
2329730
Title :
A multiobjective ant colony-based optimization algorithm for the bin packing problem with load balancing
Author :
Lara, Oscar D. ; Labrador, Miguel A.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
This paper presents ABLA, a novel multiobjective ant colony-based optimization algorithm to address the bin packing problem with load balancing. ABLA incorporates (1) a new probabilistic decision rule that builds solutions by making use of individual pheromone matrices for each objective function; (2) a new pheromone updating approach in which ants deposit variable amounts of pheromone; (3) two new local search methods to improve load balancing: LBH and LBH-AB; and (4) the Pareto dominance approach to select optimal solutions. ABLA is compared to a Multiobjective Max-Min Ant System (MO-MMAS) and an adapted multiobjective version of the First-Fit Decreasing (FFD) algorithm, which is the best known ρ-approximation algorithm for the bin packing problem. Results show that ABLA finds better solutions than both FFD and MO-MMAS, and that LBH and LBH-AB noticeably improve the load balancing across bins.
Keywords :
Pareto optimisation; approximation theory; bin packing; decision theory; resource allocation; search problems; ρ-approximation algorithm; ABLA; Pareto dominance approach; bin packing problem; first fit decreasing algorithm; load balancing; local search method; max-min ant system; multiobjective ant colony based optimization algorithm; pheromone matrix; probabilistic decision rule; Ant colony optimization; Construction industry; Heuristic algorithms; Load management; Mathematical model; Optimization; Probabilistic logic; Ant colony optimization; bin packing problem; load balancing; multiobjective optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
Type :
conf
DOI :
10.1109/CEC.2010.5586259
Filename :
5586259
Link To Document :
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