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Articles by Jen-Shiang Chen
Total Records ( 3 ) for Jen-Shiang Chen
  Ming- Cheng Lo , Jen-Shiang Chen and Yi-Chien Chen
  This study considers the problem of scheduling a set of jobs on a single Computer Numerical Control (CNC) machine where the cutting tool is subject to wear, aiming to minimize the maximum tardiness. Four mixed binary integer programming models were developed to solve this problem optimally. To solve large-sized problems, two heuristics were also developed. This study presents the computational results to demonstrate the efficiency of the models and the effectiveness of the heuristics.
  Ming-Cheng Lo , Jen-Shiang Chen and Yong-Fu Chang
  This study addresses the two-machine flow-shop scheduling problems in which both machines are versatile and thus alternative operations are possible. The performance measures are the mean flow time and makespan of jobs, respectively. The problem is formulated as two integer programming models and two heuristics are developed. Computational results are provided to demonstrate the efficiency of the models and the effectiveness of the heuristics. The integer programming technique is inefficient even for small problems. For the set of problems with known optimal solutions, the average percentage errors of heuristics H1 and H2 are within 10%, respectively. For the set of problems with unknown optimal solutions, the average percentage errors of heuristic H1 for solving the mean flow time is 20.09%, while the average percentage errors of heuristic H2 for solving the makespan is 20.84%.
  Jen-Shiang Chen
  This study considers together machine scheduling and finished product delivery. A single machine scheduling model is developed that incorporated delivery vehicle routing decisions which serves one customer location with multiple vehicles. The objective is to minimize makespan. The problem is NP-hard in the strong sense in general. A mixed binary integer programming model is developed to optimally solve this problem. Also, an illustrated example is proposed to find the optimal schedule using the proposed model.
 
 
 
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