A modified artificial bee colony algorithm for order acceptance in two-machine flow shops
We consider a two-stage make-to-order production system characterized by limited production capacity and tight order due dates. We want to make joint decisions on order acceptance and scheduling to maximize the total net revenue. The problem is computationally intractable. In view of the fact that a...
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          | Published in | International journal of production economics Vol. 141; no. 1; pp. 14 - 23 | 
|---|---|
| Main Authors | , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Amsterdam
          Elsevier B.V
    
        01.01.2013
     Elsevier Sequoia S.A  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0925-5273 1873-7579  | 
| DOI | 10.1016/j.ijpe.2012.06.003 | 
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| Abstract | We consider a two-stage make-to-order production system characterized by limited production capacity and tight order due dates. We want to make joint decisions on order acceptance and scheduling to maximize the total net revenue. The problem is computationally intractable. In view of the fact that artificial bee colony algorithm has been shown to be an effective evolutionary algorithm to handle combinatorial optimization problems, we first conduct a pilot study of applying the basic artificial bee colony algorithm to treat our problem. Based on the results of the pilot study and the problem characteristics, we develop a modified artificial bee colony algorithm. The experimental results show that the modified artificial bee colony algorithm is able to generate good solutions for large-scale problem instances.
► We consider order acceptance in two-machine flow shops. ► The net revenue of an accepted order is its revenue minus its weighted tardiness. ► The objective is to maximize the total net revenue. ► We propose a modified artificial bee colony algorithm which is able to solve large-scale problem instances effectively. | 
    
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| AbstractList | We consider a two-stage make-to-order production system characterized by limited production capacity and tight order due dates. We want to make joint decisions on order acceptance and scheduling to maximize the total net revenue. The problem is computationally intractable. In view of the fact that artificial bee colony algorithm has been shown to be an effective evolutionary algorithm to handle combinatorial optimization problems, we first conduct a pilot study of applying the basic artificial bee colony algorithm to treat our problem. Based on the results of the pilot study and the problem characteristics, we develop a modified artificial bee colony algorithm. The experimental results show that the modified artificial bee colony algorithm is able to generate good solutions for large-scale problem instances. [PUBLICATION ABSTRACT] We consider a two-stage make-to-order production system characterized by limited production capacity and tight order due dates. We want to make joint decisions on order acceptance and scheduling to maximize the total net revenue. The problem is computationally intractable. In view of the fact that artificial bee colony algorithm has been shown to be an effective evolutionary algorithm to handle combinatorial optimization problems, we first conduct a pilot study of applying the basic artificial bee colony algorithm to treat our problem. Based on the results of the pilot study and the problem characteristics, we develop a modified artificial bee colony algorithm. The experimental results show that the modified artificial bee colony algorithm is able to generate good solutions for large-scale problem instances. We consider a two-stage make-to-order production system characterized by limited production capacity and tight order due dates. We want to make joint decisions on order acceptance and scheduling to maximize the total net revenue. The problem is computationally intractable. In view of the fact that artificial bee colony algorithm has been shown to be an effective evolutionary algorithm to handle combinatorial optimization problems, we first conduct a pilot study of applying the basic artificial bee colony algorithm to treat our problem. Based on the results of the pilot study and the problem characteristics, we develop a modified artificial bee colony algorithm. The experimental results show that the modified artificial bee colony algorithm is able to generate good solutions for large-scale problem instances. ► We consider order acceptance in two-machine flow shops. ► The net revenue of an accepted order is its revenue minus its weighted tardiness. ► The objective is to maximize the total net revenue. ► We propose a modified artificial bee colony algorithm which is able to solve large-scale problem instances effectively.  | 
    
| Author | Xie, Xingzi Cheng, T.C.E. Wang, Xiuli  | 
    
| Author_xml | – sequence: 1 givenname: Xiuli surname: Wang fullname: Wang, Xiuli email: wangdu0816@163.com organization: School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China – sequence: 2 givenname: Xingzi surname: Xie fullname: Xie, Xingzi organization: School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, People's Republic of China – sequence: 3 givenname: T.C.E. surname: Cheng fullname: Cheng, T.C.E. organization: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong  | 
    
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| Snippet | We consider a two-stage make-to-order production system characterized by limited production capacity and tight order due dates. We want to make joint decisions... | 
    
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| SubjectTerms | Acceptance Algorithms Artificial bee colony algorithm Colonies Combinatorial analysis Economics Effectiveness studies Genetic algorithms Mathematical models Mathematical problems Operations research Optimization Optimization algorithms Order acceptance Pilots Production capacity Revenue Scheduling  | 
    
| Title | A modified artificial bee colony algorithm for order acceptance in two-machine flow shops | 
    
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