Browsing by Author "Lee, Wen-Chiung"

Now showing 1 - 6 of 6

A single-machine bi-criterion scheduling problem with two agents
(2013-08-01)
Lee, Wen-Chiung
;
Chung, Yu-Hsiang
;
Huang, Zong-Ren
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
The multiple-agent scheduling problems have received increasing attention recently. However, most of the research focuses on studying the computational complexity of the intractable cases or examining problems with a single criterion. Often a decision maker has to decide the schedule based on multiple criteria. In this paper, we consider a single machine problem where the objective is to minimize a linear combination of the total completion time and the maximum tardiness of jobs from the first agent given that no tardy jobs are allowed for the second agent. We develop a branch-and-bound algorithm and several simulated annealing algorithms to search for the optimal solution and near-optimal solutions for the problem, respectively. Computational experiments show that the proposed branch-and-bound algorithm could solve problems of up to 24 jobs in a reasonable amount of time and the performance of the combined simulated annealing algorithm is very good with an average error percentage of less than 0.5% for all the tested cases. (C) 2013 Elsevier Inc. All rights reserved.
Genetic algorithms for a two-agent single-machine problem with release time
(2012-11-01)
Lee, Wen-Chiung
;
Chung, Yu-Hsiang
;
Hu, Mei-Chia
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Scheduling with two competing agents has drawn a lot of attention lately. However, it is assumed that all the jobs are available in the beginning in most of the research. In this paper, we study a single-machine problem in which jobs have different release times. The objective is to minimize the total tardiness of jobs from the first agent given that the maximum tardiness of jobs from the second agent does not exceed an upper bound. Three genetic algorithms are proposed to obtain the near-optimal solutions. Computational results show that the branch-and-bound algorithm could solve most of the problems with 16 jobs within a reasonable amount of time. In addition, it shows that the performance of the combined genetic algorithm is very good with mean error percentages of less than 0.2% for all the cases. (c) 2012 Elsevier B.V. All rights reserved.
Permutation flowshop scheduling to minimize the total tardiness with learning effects
(2013-01-01)
Lee, Wen-Chiung
;
Chung, Yu-Hsiang
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Scheduling with learning effects has received considerable attention recently. Often, numbers of operations have to be done on every job in many manufacturing and assembly facilities. However, it is seldom discussed in the general multiple-machine setting, especially without the assumptions of identical processing time on all the machines or dominant machines. With the current emphasis of customer service and meeting the promised delivery dates, we consider a permutation flowshop scheduling problem with learning effects where the objective is to minimize the total tardiness. A branch-and-bound algorithm and two heuristic algorithms are established to search for the optimal and near-optimal solutions. Computational experiments are also given to evaluate the performance of the algorithms. (C) 2012 Elsevier B.V. All rights reserved.
Permutation flowshop scheduling to minimize the total tardiness with learning effects
(2013-01-01)
Lee, Wen-Chiung
;
Chung, Yu-Hsiang
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Scheduling with learning effects has received considerable attention recently. Often, numbers of operations have to be done on every job in many manufacturing and assembly facilities. However, it is seldom discussed in the general multiple-machine setting, especially without the assumptions of identical processing time on all the machines or dominant machines. With the current emphasis of customer service and meeting the promised delivery dates, we consider a permutation flowshop scheduling problem with learning effects where the objective is to minimize the total tardiness. A branch-and-bound algorithm and two heuristic algorithms are established to search for the optimal and near-optimal solutions. Computational experiments are also given to evaluate the performance of the algorithms. (C) 2012 Elsevier B.V. All rights reserved.
Single-Machine Scheduling to Minimize Total Completion Time and Tardiness with Two Competing Agents
(2014)
Lee, Wen-Chiung
;
Shiau, Yau-Ren
;
Chung, Yu-Hsiang
;
Ding, Lawson
;
工業工程與管理學系
We consider a single-machine two-agent problem where the objective is to minimize a weighted combination of the total completion time and the total tardiness of jobs from the first agent given that no tardy jobs are allowed for the second agent. A branch-and-bound algorithm is developed to derive the optimal sequence and two simulated annealing heuristic algorithms are proposed to search for the near-optimal solutions. Computational experiments are also conducted to evaluate the proposed branch-and-bound and simulated annealing algorithms.
Two-agent singe-machine scheduling with release times to minimize the total weighted completion time
(2013-01-01)
Cheng, T. C. E.
;
Chung, Yu-Hsiang
;
Liao, Shan-Ci
;
Lee, Wen-Chiung
;
應用化學系
In many management situations multiple agents pursuing different objectives compete on the usage of common processing resources. In this paper we study a two-agent single-machine scheduling problem with release times where the objective is to minimize the total weighted completion time of the jobs of one agent with the constraint that the maximum lateness of the jobs of the other agent does not exceed a given limit. We propose a branch-and-bound algorithm to solve the problem, and a primary and a secondary simulated annealing algorithm to find near-optimal solutions. We conduct computational experiments to test the effectiveness of the algorithms. The computational results show that the branch-and-bound algorithm can solve most of the problem instances with up to 24 jobs in a reasonable amount of time and the primary simulated annealing algorithm performs well with an average percentage error of less than 0.5% for all the tested cases. (C) 2012 Elsevier Ltd. All rights reserved.