Solving stochastic dynamic facility layout problems using proposed hybrid AC-CS-SA meta-heuristic algorithm

Moslemipour, Ghorbanali; Lee, Tian Soon; Loong, Y. T.

doi:10.1504/ijise.2018.088561

Cited by 5 publications

(2 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 2018, Kalita and Datta studied the constrained single-row facility layout problem using GA with large problem instances [14]. Moslemipour et al used a hybridization among ant colony, clonal selection and simulated annealing for large FLPs [15]. Feng and Chae, made the effort of solving fixed-shape rectangular layouts through the use of integer linear programming, they employed new constraints to maximize flow of material between the closed facilities [16].…”

Section: Introductionmentioning

confidence: 99%

A modified squirrel search algorithm for solving facility layout problems

Al-Saati

Algamal

2022

TELKOMNIKA

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

A modified squirrel search algorithm for solving facility layout problems

Al-Saati

Algamal

2022

TELKOMNIKA

View full text Add to dashboard Cite

show abstract

“…In Aymen and Lassâad (2012), BFOA was used in the traction and electric vehicle applications. Neural network, simulated annealing algorithm, artificial bee colony algorithm and firefly algorithm are other metaheuristics that was developed in the literature to optimise the complex problems (Fitouhi and Nourelfath, 2014;Seidgar et al, 2017;Lu et al, 2018;Moslemipour et al, 2018;Shahin and Jokar, 2018;Zhao et al, 2018;Altıntaş et al, 2019;Krishnaraj et al, 2019;Matthopoulos and Sofianopoulou, 2019).…”

Section: Introductionmentioning

confidence: 99%

A maintenance optimisation approach based on genetic algorithm for multi-component systems considering the effect of human error

Maher¹,

Aly²,

Afefy³

et al. 2022

IJISE

View full text Add to dashboard Cite

The total maintenance cost can be reduced by grouping maintenance actions of several components. This paper contributes to the existing literature by introducing an enhanced maintenance optimisation approach that considers the effect of maintenance crew loading due to grouping on the maintenance decisions of multi-component systems. A modified mathematical model is firstly developed for evaluating the failure probability function of each component, the remaining useful life and the maintenance cost. Economic and structural dependencies are taken into consideration. A simulation is secondly implemented to provide estimates of the associated costs with changes in the decision variables. Using the simulation model, an optimisation approach based on a genetic algorithm is thirdly developed to minimise the long-term mean maintenance cost per unit time. Computational results show that the proposed maintenance optimisation approach provides considerable maintenance cost savings and emphasises the importance of considering the effect of maintenance crew constraints in maintenance scheduling.

show abstract