A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangement
This paper presents the hybrid Particle Swarm Optimization and the Variable Neighborhood Search (PSO-VNS) to solve the machinery and equipment allocation and scheduling to help the growers expand the production level to meet the increased demands and growing interest, and to increase profitability....
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| Format: | Article |
| Language: | English |
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Elsevier
2023-05-01
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| Series: | Intelligent Systems with Applications |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305323000315 |
| _version_ | 1797804534111666176 |
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| author | Kongkidakhon Worasan Kanchana Sethanan Rapeepan Pitakaso Thitipong Jamrus Karn Moonsri Paulina Golinska-Dawson |
| author_facet | Kongkidakhon Worasan Kanchana Sethanan Rapeepan Pitakaso Thitipong Jamrus Karn Moonsri Paulina Golinska-Dawson |
| author_sort | Kongkidakhon Worasan |
| collection | DOAJ |
| description | This paper presents the hybrid Particle Swarm Optimization and the Variable Neighborhood Search (PSO-VNS) to solve the machinery and equipment allocation and scheduling to help the growers expand the production level to meet the increased demands and growing interest, and to increase profitability. This problem can be formulated as the Machinery and Equipment Allocation and Scheduling Problem (MEASP) which is special type of a hybrid flow shop scheduling problem (HFS) with sequence dependent setup times, machine eligibility, machine grouping, blocking, tooling constraint, and time windows (HFS |SDST, rcrc, Grouping, blocking, Tool, Tw | Cmax). The objective of this research is to minimize the total completion time for sugarcane cultivation. A Mixed Integer Linear Programming (MILP) model was developed to handle small-scale problems. The hybrid Particle Swarm Optimization and the Variable Neighborhood Search (PSO-VNS) was used for large-scale problems. Two new velocity update formulae and a position update formula were incorporated into the Particle Swarm Optimization (PSO), and four types of neighborhood strategies were developed for the VNS. The experimental results show that all the PSO-VNS methods outperform the traditional PSO due to the effectiveness of the newly proposed velocity and position update formulae in finding the optimal solutions, the PSO-VNS-6 methods, on the average, can reduce the computational time by 58.43% from the original PSO and improve the solution quality by 11.71%. |
| first_indexed | 2024-03-13T05:38:38Z |
| format | Article |
| id | doaj.art-71e19491a02c4a518575d5882014e3ea |
| institution | Directory Open Access Journal |
| issn | 2667-3053 |
| language | English |
| last_indexed | 2024-03-13T05:38:38Z |
| publishDate | 2023-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Intelligent Systems with Applications |
| spelling | doaj.art-71e19491a02c4a518575d5882014e3ea2023-06-14T04:34:49ZengElsevierIntelligent Systems with Applications2667-30532023-05-0118200206A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangementKongkidakhon Worasan0Kanchana Sethanan1Rapeepan Pitakaso2Thitipong Jamrus3Karn Moonsri4Paulina Golinska-Dawson5Faculty of Business Administration and Accountancy, Khon Kaen University, Khon Kaen 40002, ThailandResearch Unit on System Modeling for Industry, Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand; Corresponding author.Metaheuristics for Logistic Optimization Laboratory, Department of Industrial Engineering, Faculty of Engineering, Ubon Ratchathani University, Ubon Ratchathani, ThailandResearch Unit on System Modeling for Industry, Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, ThailandDepartment of Logistics Engineering, Faculty of Engineering, Nakhon Phanom University, Nakhon Phanom, ThailandFaculty of Engineering Management, Poznan University of Technology, 2 Jacka Rychlewskiego Str., Poznan 60-965, PolandThis paper presents the hybrid Particle Swarm Optimization and the Variable Neighborhood Search (PSO-VNS) to solve the machinery and equipment allocation and scheduling to help the growers expand the production level to meet the increased demands and growing interest, and to increase profitability. This problem can be formulated as the Machinery and Equipment Allocation and Scheduling Problem (MEASP) which is special type of a hybrid flow shop scheduling problem (HFS) with sequence dependent setup times, machine eligibility, machine grouping, blocking, tooling constraint, and time windows (HFS |SDST, rcrc, Grouping, blocking, Tool, Tw | Cmax). The objective of this research is to minimize the total completion time for sugarcane cultivation. A Mixed Integer Linear Programming (MILP) model was developed to handle small-scale problems. The hybrid Particle Swarm Optimization and the Variable Neighborhood Search (PSO-VNS) was used for large-scale problems. Two new velocity update formulae and a position update formula were incorporated into the Particle Swarm Optimization (PSO), and four types of neighborhood strategies were developed for the VNS. The experimental results show that all the PSO-VNS methods outperform the traditional PSO due to the effectiveness of the newly proposed velocity and position update formulae in finding the optimal solutions, the PSO-VNS-6 methods, on the average, can reduce the computational time by 58.43% from the original PSO and improve the solution quality by 11.71%.http://www.sciencedirect.com/science/article/pii/S2667305323000315Sharing resource systemSugarcaneSchedulingTooling constraintBlocking constraintMachine restriction |
| spellingShingle | Kongkidakhon Worasan Kanchana Sethanan Rapeepan Pitakaso Thitipong Jamrus Karn Moonsri Paulina Golinska-Dawson A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangement Intelligent Systems with Applications Sharing resource system Sugarcane Scheduling Tooling constraint Blocking constraint Machine restriction |
| title | A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangement |
| title_full | A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangement |
| title_fullStr | A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangement |
| title_full_unstemmed | A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangement |
| title_short | A hybridization of PSO and VNS to solve the machinery allocation and scheduling problem under a machinery sharing arrangement |
| title_sort | hybridization of pso and vns to solve the machinery allocation and scheduling problem under a machinery sharing arrangement |
| topic | Sharing resource system Sugarcane Scheduling Tooling constraint Blocking constraint Machine restriction |
| url | http://www.sciencedirect.com/science/article/pii/S2667305323000315 |
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