Greedy mechanism-based bi-objective optimization for green scheduling in manufacturing systems considering transportation

This paper addresses scheduling challenges in hybrid flow manufacturing systems with crane transportation (HFMS-CT) driven by intelligent control, mass customization, and eco-friendly manufacturing. Unlike previous studies, it considers the interdependence between machine processing and crane transp...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Applied soft computing Ročník 175; s. 113093
Hlavní autoři: Wang, Zhu, Qiu, Rongping, Zhou, Binghai
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.05.2025
Témata:
Conflict analysis
Epsilon-constraint
Green scheduling
Harris Hawk optimization algorithm
Hybrid flow manufacturing systems with crane transportation
Epsilon-constraint
Hybrid flow manufacturing systems with crane transportation
Harris Hawk optimization algorithm
Green scheduling
Conflict analysis
ISSN:1568-4946
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper addresses scheduling challenges in hybrid flow manufacturing systems with crane transportation (HFMS-CT) driven by intelligent control, mass customization, and eco-friendly manufacturing. Unlike previous studies, it considers the interdependence between machine processing and crane transport, focusing on minimizing both makespan and energy consumption. A bi-objective mixed-integer programming model is developed, and the Epsilon-constraint method is used for small-scale cases. Given the NP-hardness, a modified multi-objective Harris Hawk optimization (MMOHHO) is proposed. It adopts greedy mechanisms by integrating Laplace crossover, tent-based chaotic mapping, elite selection, and nonlinear optimization strategy to balance exploration and exploitation capabilities. The proposed algorithm is compared with the Epsilon-constraint method and benchmark metaheuristics. The experimental results reveal that the proposed algorithm outperforms other methods regarding NPS, DPO, IGD, and ES evaluation metrics. Finally, an in-depth discussion is conducted using a real-world case study, offering valuable managerial insights and practical recommendations for implementation. ●The crane transporting path and conflict are considered in the hybrid flow manufacturing system (HFMS) scheduling problem.●A bi-objective MIP model with minimizing makespan and energy consumption is formulated.●Multi-objective Harris Hawk optimization algorithm is improved with hybrid strategies designed by the characteristics of bi-objective HFMS scheduling problem.●Greedy mechanism is introduced to enhance exploitation strategy during iteration.●The proposed algorithm is validated to be superior to Epsilon constraint method, MOGWO, and MOPSO.
ISSN:1568-4946
DOI:10.1016/j.asoc.2025.113093