Development of an Adaptive Genetic Algorithm to Optimize the Problem of Unequal Facility Location

• Autorzy: Budi Hendrik Setia , Elveny Marischa , Zhuravlev Pavel , Jalil Abduladheem Turki , Al-Janabi Samaher , Alkaim Ayad F. , Saleh Marwan Mahmood , Shichiyakh Rustem Adamovich , Sutarto

Identyfikatory

DOI

10.2478/fcds-2022-0006

• Języki publikacji: EN

Abstrakty

EN

The problem of unequal facility location involves determining the location of a set of production equipment whose dimensions are different, as well as the interrelationships between each of them. This paper presents an efficient method for optimizing the problem of unequal facility layouts. In this method, the genetic algorithm is improved and developed into an adaptive genetic algorithm. In this algorithm, the mutation operator is applied only when the similarity of chromosomes in each population reaches a certain level. This intelligence prevents jumps in situations where they are not needed and reduces computational time. In order to measure the performance of the proposed algorithm, its performance is compared with the performance of conventional genetic algorithms and refrigeration simulators. Computational results show that the adaptive genetic algorithm is able to achieve higher-quality solutions.

Słowa kluczowe

EN

unequal facility location; interactions; Adaptive Genetic Algorithm; Mutation Operator Intelligence; healthy lifestyle

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2022
• Tom: Vol. 47, No. 2
• Strony: 111--125
• Opis fizyczny: Bibliogr. 22 poz., rys., tab., wykr.

Twórcy

autor

Budi Hendrik Setia

• Department of Oral Biology, Faculty of Dental Medicine, Universitas Airlangga, Surabaya, Indonesia

• https://orcid.org/0000-0002-5518-3372

autor

Elveny Marischa

• DS & CI Research Group Universitas, Sumatera Utara, Medan

• https://orcid.org/0000-0001-5702-8846

autor

Zhuravlev Pavel

• Plekhanov Russian University of Economics, Russian Federation

• https://orcid.org/0000-0002-6061-9935

autor

Jalil Abduladheem Turki

• Medical Laboratories Techniques Department, Al-Mustaqbal University College, Babylon, Hilla, Iraq

• https://orcid.org/0000-0001-8403-7465

autor

Al-Janabi Samaher

• College of science for women University of Babylon, Iraq

• https://orcid.org/0000-0003-2811-1493

autor

Alkaim Ayad F.

• College of science for women University of Babylon, Iraq

• https://orcid.org/0000-0003-3459-4583

autor

Saleh Marwan Mahmood

• University of Anbar

• https://orcid.org/0000-0003-2034-0128

autor

Shichiyakh Rustem Adamovich

• Kuban State Agrarian University named after I.T. Trubilin, Department of Management, Krasnodar, Krasnodar

• https://orcid.org/0000-0002-5159-4350

autor

Sutarto

• Mathematics Education, Faculty of Science, Engineering and Applied, Universitas Pendidikan Mandalika, Indonesia

Bibliografia

• [1] Garey, M.R., Johnson, D.S. (1999). Computers and intractability: A guide to the theory of NP-completeness. New York: WH Freeman.
• [2] Guan J., Lin G. (2011). Hybridizing variable neighborhood search with ant colony optimization for solving the single row facility layout problem, European Journal of Operational Research TEA (C), 499–9.9.
• [3] McKendall, A.R., Shang, J. (2009). Hybrid ant systems for the dynamic facility layout problems, Computers and Operations Research 33: 790-803.
• [4] Nee A.Y.C., Jiang S. (2013). A novel facility layout planning and optimization methodology, CIRP Annals-Manufacturing Technology 62, 483-486.
• [5] Neghabi, H., Tari, F.G. (2016). A new concept of adjacency for concurrent consideration of economic and safety aspects in design of facility layout problems, Journal of Loss Prevention in the Process Industries 40, 603-614.
• [6] Paes, F.G., Pessoa, A.A., Vidal, T. (2017). A hybrid genetic algorithm with decomposition phases for the Unequal Area Facility Layout Problem, European Journal of Operational Research 256(3), 742-756.
• [7] Samarghandi, H., Eshghi, K. (2010). An efficient tabu algorithm for the single row facility layout problem. European Journal of Operational Research, 205: 98-105.
• [8] Ulutas B., Islier A. (2010). Dynamic facility layout problem in footwear industry, Journal of Manufacturing Systems 36, 55-61.
• [9] Urban, T.L. (1993). A heuristic for the dynamic facility layout problem. IIE Transactions 25(4): 57-63.
• [10] Xu, J., Song, X. (2010). Multi-objective dynamic layout problem for temporary construction 4 facilities with | unequal-area departments under fuzzy random, Knowledge-Based Systems, 81: 30-45.
• [11] Wang, S., Zuoa, X., Liua, X., Zhaoc, X., Li, J. (2015). Solving dynamic double row layout problem via combining simulated annealing and mathematical programming, Applied Soft Computing 37, 303-310.
• [12] Shavarani, S.M., Nejad, M. G. Rismanchian, F., & Izbirak, G. (2018). Application of hierarchical facility location problem for optimization of a drone delivery system: a case study of Amazon prime air in the city of San Francisco. The International Journal of Advanced Manufacturing Technology, 95(9), 3141-3153.
• [13] Guo, Q., & Kluse, C. (2020). A framework of photovoltaics recycling facility location optimization. Sustainable Production and Consumption, 23, 105-110.
• [14] Fu, Y., Wu, D., Wang, Y., & Wang, H. (2020). Facility location and capacity planning considering policy preference and uncertain demand under the One Belt One Road initiative. Transportation Research Part A: Policy and Practice, 138, 172-186. [
• 15] Shan, W., Yan, Q., Chen, C., Zhang, M., Yao, B., & Fu, X. (2019). Optimization of competitive facility location for chain stores. Annals of Operations Research, 273(1-2), 187-205.
• [16] Saif, A., & Delage, E. (2021). Data-driven distributionally robust capacitated facility location problem. European Journal of Operational Research, 291(3), 995-1007.
• [17] Fakhrzad, M.B., Amir M.G., and Farzaneh B. (2015). "A mathematical model for P-hub median location problem to multiple assignments between non-hub to hub nodes under fuzzy environment." Journal of Management and Accounting Studies 3, 2, 61-67.
• [18] Ahmadi-Javid A, Ardestani-Jaafari A. (2021). The unequal area facility layout problem with shortest single-loop AGV path: how material handling method matters. International Journal of Production Research, 59(8), 2352-74.
• [19] Zouein P.P., Kattan S. (2021). An improved construction approach using ant colony optimization for solving the dynamic facility layout problem. Journal of the Operational Research Society. 29, 1-5.
• [20] Bhuiyan, T.H., Harun, S., & Azeem, A. (2021). Development of an optimisation model for unequal-area facility layout problems. International Journal of Industrial and Systems Engineering, 37(1), 27-45.
• [21] Liu, J., Liu, S., Liu, Z., & Li, B. (2020). Configuration space evolutionary algorithm for multi-objective unequal-area facility layout problems with flexible bays. Applied Soft Computing, 89, 106052.
• [22] García-Hernández, L., Salas-Morera, L., Carmona-Muñoz, C., Garcia-Hernandez, J.A., & Salcedo-Sanz, S. (2020). A novel island model based on coral reefs optimization algorithm for solving the unequal area facility layout problem. Engineering Applications of Artificial Intelligence, 89, 103445.