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An Ant Colony Optimization Algorithm for the Two-stage Knapsack Problem
Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory. Linköping University, The Institute of Technology.
2011 (English)In: Proceedings of the 10th Biennial International Conference on Artificial Evolution / [ed] Jin-Kao Hao, Pierrick Legrand, Pierre Collet, Nicolas Monmarché, Evelyne Lutton, Marc Schoenauer, 2011, 166-179 p.Conference paper (Refereed)
Abstract [en]

We propose an Ant Colony Optimization algorithm for the Two-Stage Knapsack problem with discretely distributed weights and capacity. To the best of our knowledge this is the first attempt to solve a Two-Stage Knapsack problem using a metaheuristic. Two heuristic utility measures are proposed and compared. Moreover, we introduce the novel idea of non-utility measures in order to obtain a criterion for the construction termination. We argue why for the proposed measures it is more efficient to place pheromone on arcs instead of vertices or edges of the complete search graph. Numerical tests show that our algorithmis able to produce, in much shorter computing time, solutions of similar quality than CPLEX after 2h. Moreover, with increasing number of scenarios the percentage of runs where our algorithm is able to produce better solutions than CPLEX (after 2h) increases.

Place, publisher, year, edition, pages
2011. 166-179 p.
National Category
Computer Science
URN: urn:nbn:se:liu:diva-74516ISBN: 978-2-9539267-1-2OAI: diva2:486439
10th Biennial International Conference on Artificial Evolution (EA-2011)
Available from: 2012-01-30 Created: 2012-01-30 Last updated: 2012-02-07

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Kosuch, Stefanie
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