Green manufacturing: Order acceptance and scheduling subject to the budgets of energy consumption and machine launch

This paper investigates an order acceptance and scheduling problem with an energy consumption budget, a machine launch budget, and the order release time in a green manufacturing system. The phenomenon of deteriorating jobs is considered in the production of the accepted orders. The objective of the...

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Vydáno v:Journal of cleaner production Ročník 248; s. 119300
Hlavní autoři: Kong, Min, Pei, Jun, Liu, Xinbao, Lai, Pei-Chun, Pardalos, Panos M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.03.2020
Témata:
algorithms
dynamic programming
Dynamic programming algorithm
employment
energy
income
manufacturing
Modified variable neighborhood search
Order acceptance
Parallel machines selection
sustainable manufacturing
Dynamic programming algorithm
Order acceptance
Modified variable neighborhood search
Parallel machines selection
ISSN:0959-6526, 1879-1786
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Shrnutí:This paper investigates an order acceptance and scheduling problem with an energy consumption budget, a machine launch budget, and the order release time in a green manufacturing system. The phenomenon of deteriorating jobs is considered in the production of the accepted orders. The objective of the study is to maximize the net revenue and a modified variable neighborhood search (MVNS) Algorithm that combines a novel encoding and decoding procedure as well as a dynamic programming algorithm is developed to solve it. To show the effectiveness and efficiency of the proposed algorithm, we first employ the MVNS algorithm and seven VNS-based algorithms to solve the problems with different configurations of orders and machines. The results show that the MVNS algorithm obtains better solutions than existing VNS-based algorithms. Then, the proposed algorithm is compared with three meta-heuristic algorithms. The experimental results show that the proposed algorithm has significant advantages in terms of solution optimality.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2019.119300