Abstract
Beetle antennae search (BAS) algorithm is a newly proposed single-solution based metaheuristic technique inspired by the beetle preying process. Although BAS algorithm has shown good search abilities, it can be easily trapped into local optimum when it is used to solve hard optimization problems. With the intention to overcome this drawback, this paper presents a population-based beetle antennae search (PBAS) algorithm for solving integer programming problems. This method employs the population's capability to search diverse regions of the search space to provide better guarantee for finding the optimal solution. The PBAS method was tested on nine integer programming problems and one mechanical design problem. The proposed algorithm was compared to other state-of-the-art metaheuristic techniques. The comparisons show that the proposed PBAS algorithm produces better results for majority of tested problems.
Highlights
A discrete optimization problem where all the variables are restricted to integer values is an integer programming problem
With the intention to overcome this drawback, this paper presents a population-based beetle antennae search (PBAS) algorithm for solving integer programming problems
The PBAS algorithm was tested on nine integer programming problems and one mechanical design problem
Summary
A discrete optimization problem where all the variables are restricted to integer values is an integer programming problem. Single-solution based metaheuristic methods, such as simulated annealing or recently proposed beetle antennae search (BAS) algorithm focus on enhancing a single potential solution. According to the diverse information of antennas, the beetle updates the flight direction and potentially reaches the food This method is mostly applied to the optimization of single-objective problems, and it has local optimization performance (Zhang et al, 2021). The BAS algorithm is recently developed metaheuristic method which has shown good performance for solving certain optimization problems. The main contribution of this study is development of a population-based beetle antennae search (PBAS) algorithm for solving integer programming problems. The PBAS employs the population's capability to search different regions of the search space This method was tested on nine well-known integer programming problems and one mechanical design problem.
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