Reproduction operators in solving LABS problem using EMAS meta-heuristic with various local optimization techniques

Abstract

ABSTRACT Agent-based evolutionary, computational systems have been proven to be an efficient concept for solving complex computational problems. This paper is an extension of [Biełaszek, S., Piętak, K., & Kisiel-Dorohinicki, M. (2021). New extensions of reproduction operators in solving LABS problem using EMAS meta-heuristic. Springer, cop. 2021. – Lecture Notes in Artificial Intelligence, Computational collective intelligence 12876 304-316. 13th International Conference, ICCCI 2021: Rhodes, Greece, September 29ŰOctober 1, 2021.] where we proposed new variants of reproduction operators together with new heuristics for the generation of initial population, dedicated to LABS – a hard discrete optimization problem. In this research, we verify if the proposed recombination operators improve EMAS efficiency also with different local optimization techniques such as Tabu Search and Self-avoiding walk, and therefore can be seen as better recombination operators dedicated to LABS problem in general. This paper recalls the definition of new recombination variants dedicated to LABS and verify if they can be successfully used in many different evolutionary configurations.