Research Information System
IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), France, 1 - 03 December 2015
In most of the optimization studies, the problem related data is assumed to be exactly known beforehand and remain stationary throughout whole optimization process. However, majority of real life problems and their practical applications are dynamic in their nature due to the reasons arising from unpredictable events, such as rush orders, fluctuating capacities of manufacturing constraints, changes in costs or profits. A problem, carrying one of these features is known as dynamic optimization problem (DOP) in the related literature. In DOPs the aim is not only to find the optimum of the current problem configuration, but to keep track of the moving optima. Dynamic optimization is a hot research area and a notable variety of solution methodologies are developed for DOPs in the past decade. As a contribution to the existing literature of DOPs, in the current work, the idea of using a multi-start and constructive search algorithm and thus breaking the dependency to the previously found solutions is presented. The performance tests are conducted on the generalized assignment problem, which has numerous real life applications. In regard to the obtained results, the proposed method is found promising.