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A simheuristic appr...
A simheuristic approach towards supply chain scheduling : Integrating production, maintenance and distribution
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- Rabet, Rahmat (författare)
- Department of Industrial Engineering, Islamic Azad University Science and Research Branch, Tehran, Iran
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- Ganji, Maliheh (författare)
- Department of Industrial Engineering, Islamic Azad University Central Tehran branch, Tehran, Iran
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- Fathi, Masood (författare)
- Högskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala, Sweden,Virtual Production Development (VPD)
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(creator_code:org_t)
- Elsevier, 2024
- 2024
- Engelska.
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Ingår i: Applied Soft Computing. - : Elsevier. - 1568-4946 .- 1872-9681. ; 153
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- This study attempts to integrate production, maintenance, and delivery operations among supply chain members. Despite numerous studies in the field of supply chain management, researchers have often overlooked crucial aspects, such as uncertainties in demand and production. For instance, the significant impact of maintenance activities on production flow has been underrepresented in supply chain management literature. This study investigates these gaps in the context of a fertilizer producer case study, which is characterized by seasonal demand and the functional silos syndrome due to old-fashioned management approaches. This study proposes a mathematical model and two multi-objective simheuristics for the Integrated Production, Maintenance, and Distribution Scheduling Problem (IPMDSP) considering demand variation for multiple products and product delivery time-windows using a heterogeneous fleet of vehicles. The IPMDSP is solved using the ϵ-constraint method and simheuristics linking the simulation model to customized and tuned versions of Particle Swarm Optimization (MOPSO) and the Non-dominated Sorting Genetic Algorithm (NSGA-II). The optimization objectives include minimizing maintenance duration, distribution costs, and customer dissatisfaction due to delivery tardiness. The results demonstrate the superiority of the simheuristic empowered by NSGA-II over the MOPSO in solving the IPMDSP. The comparison between the performance of deterministic and stochastic approaches in addressing the problem reveals that neglecting uncertainty caused by maintenance activities can lead to an increase in optimization objectives. Furthermore, the proposed simheuristics achieved significant improvements in minimizing objectives in solving the fertilizer producer case study.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Annan samhällsbyggnadsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Other Civil Engineering (hsv//eng)
Nyckelord
- Distribution
- Heterogeneous vehicles routing problem
- Integrated supply chain
- Maintenance
- Simheuristic
- Fertilizers
- Fleet operations
- Genetic algorithms
- Heuristic algorithms
- Particle swarm optimization (PSO)
- Screening
- Stochastic systems
- Supply chain management
- Heterogeneous vehicle routing problem
- Heterogeneous vehicles
- Integrated maintenance
- Integrated production
- Production distribution
- Production Scheduling
- Vehicle Routing Problems
- Virtual Production Development (VPD)
- Virtual Production Development (VPD)
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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