A modified squirrel search algorithm for solving facility layout problems

Abstract

With the huge advance in artificial intelligence and the rapid development of intelligent swarm algorithms, the exploration of facility layout problem (FLP) with its non-deterministic polynomial-time (NP-Hard) nature has gained much more attention. The squirrel search algorithm is one of the swarm algorithms that is known for its effective gliding feature that provides cheap exploration of lengthy distances. In this work, Msqrl algorithm is presented as a modification of squirrel search algorithm to be capable of handling permutation-specific FLP. The modification is done by introducing two new operators: Msqrl-Exchange and Msqrl-Winter. It is used to investigate the effectiveness in finding acceptable solutions to variable-size, single-row FLPs in a fast and efficient manner. Tests included small and large benchmark instances for comparisons. Outcomes show that Msqrl was able to improved quite a few previously found solutions by acting efficiently and converging rapidly to solutions. It outperformed both semidefinite programming and cuckoo optimization in finding optimal solutions in an acceptable number of iterations and relatively small population sizes.

Optimal backstepping controller for controlling DC motor speed

“…The squirrel search algorithm (SSA) was a novel optimization method proposed by Jain et al [20], it assumes that (n) flying squirrels have (n) deciduous trees in the search space, each squirrel have one tree and the manner of searching is done individually, tree types is classified into three (normal, oak or acorn nuts and hickory) and the final assumptions is that three trees is classified as oak tree and one as hickory. The location vector for each ith flying squirrel is defined as follows [21]- [23]:…”