Genetic algorithms (GAs) have been used to evolve optimal/sub-optimal solutions of many problems. When using GAs for evolving solutions, often fitness evaluation is the most computationally expensive, and this discourages researchers from applying challenging This paper presents an approach generating offspring based on a local landscape exploration increase speed search better solutions. The p...

This paper proposes two algorithms for clustering data, which are variable-sized sets of elementary items. An example such data occurs in the analysis a medical diagnosis, where goal is to detect human subjects who share common diseases possibly predict future illnesses from previous history. The first proposed algorithm based on K-medoids and second extends random swap algorithm, has proven be...

This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA a...