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

被引:30
作者
Kong, Min [1 ,2 ,4 ]
Pei, Jun [1 ,2 ,3 ]
Liu, Xinbao [1 ,2 ]
Lai, Pei-Chun [5 ]
Pardalos, Panos M. [3 ]
机构
[1] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
[2] Minist Educ, Key Lab Proc Optimizat & Intelligent Decis Making, Hefei 230009, Peoples R China
[3] Univ Florida, Dept Ind & Syst Engn, Ctr Appl Optimizat, Gainesville, FL 32611 USA
[4] Texas A&M Univ, Dept Ind & Syst Engn, College Stn, TX 77843 USA
[5] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA
基金
中国国家自然科学基金;
关键词
Parallel machines selection; Order acceptance; Modified variable neighborhood search; Dynamic programming algorithm; VARIABLE NEIGHBORHOOD SEARCH; FLEXIBLE JOB-SHOP; OPTIMIZATION ALGORITHM; SELECTION; NUMBER; EVOLUTIONARY; TARDINESS; TIMES;
D O I
10.1016/j.jclepro.2019.119300
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (c) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:17
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