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A New Primal-Dual Genetic Algorithm: Case Study for the Winner Determination Problem

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6022))

Abstract

This paper presents a new evolutionary computing strategy which uses the linear programming duality information to help the search for optimum solutions of hard optimization problems. The algorithm is restarted several times when it is stuck into a local optima. At each restart, the appropriate dual space is constructed. A new population of primal individuals is generated using the information from dual solutions and is considered for next iterations. The pursued goal was not to find the best algorithm for solving winner determination problem, but to prove the method’s viability using the problem as a case study. Experiments on realistic instances were performed.

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Raschip, M., Croitoru, C. (2010). A New Primal-Dual Genetic Algorithm: Case Study for the Winner Determination Problem. In: Cowling, P., Merz, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2010. Lecture Notes in Computer Science, vol 6022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12139-5_22

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  • DOI: https://doi.org/10.1007/978-3-642-12139-5_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12138-8

  • Online ISBN: 978-3-642-12139-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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