Population-based metaheuristic algorithms normally manage a large number of ‘individuals’ to achieve diversity in the search process, which in turn lead to good quality solutions. Although the quality of the solutions produced by these algorithms is observed to be good for a variety of combinatorial optimization problems, managing a large number of individuals within the algorithm is often complex and time-consuming. In this paper, we develop a two-individual based path relinking (TPR) algorithmic framework harnessing the power of the solution-based tabu search and that of a distance-controlled relinking operator to solve the satellite broadcast scheduling problem (SBSP). The results of extensive computational experiments carried out demonstrate that our TPR algorithm outperforms state-of-the-art heuristic algorithms for SBSP with respect to various performance metrics, in a statistically significant way. The aim of this study is to compare the two-individual based search algorithm with the traditional population-based metaheuristic methods in the literature for the SBSP (i.e., ant colony optimization and differential evolution variant algorithms) to provide a highly competitive algorithm for solving this important practical problem with numerous applications, and to promote research on two-individual based search method, which received very little attention in the literature. Our results underscore that the two-individual based search algorithmic framework is a viable alternative for solving complex optimization problems and reconfirm the validity of analogous observations made by other researchers in the context of graph coloring and flexible job shop scheduling.
- Evolutionary algorithm
- Satellite broadcast scheduling
- Solution-based tabu search
ASJC Scopus subject areas
- Management Information Systems
- Information Systems and Management
- Artificial Intelligence