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

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

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
EditorsH A Abbass, T Bossomaier, J Wiles
Place of PublicationSydney
PublisherWorld Scientific
Pages215-226
Number of pages12
Volume3
ISBN (Electronic)978-981-270-149-7
ISBN (Print)978-981-256-615-7
DOIs
Publication statusPublished - 2005

Fingerprint

Dynamic optimization
Knapsack problem
Ant colony optimization
Optimization problem
Problem solving
Prototype
Manufacturing
Telecommunications
Metaheuristics
Heuristic search

Cite this

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 (Vol. 3, pp. 215-226). Sydney: World Scientific. https://doi.org/10.1142/9789812701497_0016
Randall, Marcus. / A dynamic optimisation approach for ant colony optimisation using the multidemsional knapsack problem. Recent Advances in Artificial Life. editor / H A Abbass ; T Bossomaier ; J Wiles. Vol. 3 Sydney : World Scientific, 2005. pp. 215-226
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Randall, M 2005, A dynamic optimisation approach for ant colony optimisation using the multidemsional knapsack problem. in HA Abbass, T Bossomaier & J Wiles (eds), Recent Advances in Artificial Life. vol. 3, World Scientific, Sydney, pp. 215-226. https://doi.org/10.1142/9789812701497_0016

A dynamic optimisation approach for ant colony optimisation using the multidemsional knapsack problem. / Randall, Marcus.

Recent Advances in Artificial Life. ed. / H A Abbass; T Bossomaier; J Wiles. Vol. 3 Sydney : World Scientific, 2005. p. 215-226.

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

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Randall M. A dynamic optimisation approach for ant colony optimisation using the multidemsional knapsack problem. In Abbass HA, Bossomaier T, Wiles J, editors, Recent Advances in Artificial Life. Vol. 3. Sydney: World Scientific. 2005. p. 215-226 https://doi.org/10.1142/9789812701497_0016