Organizing sports matches with a hybrid monkey search algorithm

This academic piece of the paper illustrates an approach of organizing sports matches to be as a tool of sports schedule maker via a proposed hybrid Monkey search algorithm by doubles elimination tournament. Input are a set of teams represented by monkeys. It states that the natural behavior of monkeys and its climbing to obtain (solution) through uphill (climbing), watch-jumping, and somersault process. The parameters in the climb were represented by whether or not sports team won. The distribution of the teams, whether in the upper or the lower half, represented in the watch-jumping by mathematical equations, in addition to representing the variables in somersault process. The consequences behind the suggested algorithm used have tackled steps to reach an optimal schedule for a variety of teams for the same championship. The team cannot play more than two consecutive matches with the condition of starting with a random population of feasible solutions. The performance of the presented algorithm was very well through providing a flexible and easy organization of sports matches without using classic or manual routine. Furthermore, the search space reduced so that can give a guarantee to achieve a globally optimum solution. The software platform was MATLAB m-files.

An Improved Monkey Search Algorithm to Solve the Flexible Job Shop Scheduling Problems With Makespan Objective

This work proposes a hybrid monkey search algorithm (HMSA) to solve the flexible job shop scheduling problem (FJSP) to minimize the makespan. The FJSP is a simple scheduling model that resembles numerous industrial production processes and the FJSP has been proved to be strongly NP-hard. Due to both theoretical and practical significance of FJSP, numerous researchers tackled the FJSP using different approaches. In this paper, the variable neighbourhood search (VNS) algorithm is combined with the monkey search algorithm (MSA) to enhance the solution quality. Benchmark problems are considered for validating the performance of the proposed algorithm. The computational results confirm the supremacy of the proposed HMSA for the benchmark problem.