A dynamic optimisation approach for ant colony optimisation using the multidemsional knapsack problem

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Abstract

Meta-heuristic search techniques have been extensively applied to static optimisation problems. These are problems in which the definition and/or the data remain fixed throughout the process of solving the problem. Many real-world problems, particularly in transportation, telecommunications and manufacturing, change over time as new events occur, thus altering the solution space. This paper explores methods for solving these problems with ant colony optimisation. A method of adapting the general algorithm to a range of problems is presented. This paper shows the development of a small prototype system to solve dynamic multidimensional knapsack problems. This system is found to be able to rapidly adapt to problem changes.
Original languageEnglish
Title of host publicationRecent Advances in Artificial Life: Advances in Natural Computation: Volume 3
Subtitle of host publication Sydney, Australia, 5 – 8 December 2005
EditorsH A Abbass, T Bossomaier, J Wiles
Place of PublicationSingapore
PublisherWorld Scientific
Chapter16
Pages215-226
Number of pages12
ISBN (Electronic)978-981-270-149-7
ISBN (Print)978-981-256-615-7 , 9812566155
DOIs
Publication statusPublished - 2005

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    Randall, M. (2005). A dynamic optimisation approach for ant colony optimisation using the multidemsional knapsack problem. In H. A. Abbass, T. Bossomaier, & J. Wiles (Eds.), Recent Advances in Artificial Life: Advances in Natural Computation: Volume 3: Sydney, Australia, 5 – 8 December 2005 (pp. 215-226). World Scientific. https://doi.org/10.1142/9789812701497_0016