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.
|Title of host publication||Recent Advances in Artificial Life: Advances in Natural Computation: Volume 3|
|Subtitle of host publication||Sydney, Australia, 5 – 8 December 2005|
|Editors||H A Abbass, T Bossomaier, J Wiles|
|Place of Publication||Singapore|
|Number of pages||12|
|ISBN (Print)||978-981-256-615-7 , 9812566155|
|Publication status||Published - 2005|