• 산업공학
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• 제12권4호
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• pp.617-624
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• 1999

In order to maximize an availability of machine and utilization of space, the parallel machines scheduling problem with space limit is frequently discussed in the industrial field. In this paper, we consider a scheduling problem for assembly machine in ship engine assembly shop. This paper considers the parallel machine scheduling problem in which n jobs having different release times, due dates and space limits are to be scheduled on m parallel machines. The objective function is to minimize the sum of earliness and tardiness. To solve this problem, a heuristic is developed. The proposed heuristic is divided into three modules hierarchically: job selection, machine selection and job sequencing, solution improvement. To illustrate its effectiveness, a proposed heuristic is evaluated with a large number of randomly generated test problems based on the field situation. Through the computational experiment, we determine the job selection rule that is suitable to the problem situation considered in this paper and show the effectiveness of our heuristic.

• Industrial Engineering and Management Systems
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• 제3권2호
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• pp.100-115
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• 2004

The network representation and branch and bound algorithm with efficient lower and upper bounding procedures are developed to determine a global optimal production schedule on a machine that minimizes sequence-dependent setup cost and earliness/tardiness penalties. Lower bounds are obtained based on heuristic and Lagrangian relaxation. Priority dispatching rule with local improvement procedure is used to derive an initial upper bound. Two dominance criteria are incorporated in a branch and bound procedure to reduce the search space and enhance computational efficiency. The computational results indicate that the proposed procedure could optimally solve the problem with up to 40 jobs in a reasonable time using a personal computer.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.295-298
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• 1996

We consider a nonpreemptive single-machine scheduling problem to minimize the mean squared deviation(MSD) of job completion times about a common due date d with a maximum tardiness constraint, i.e., maximum tardiness is less than or equal to the given allowable amount, .DELTA.(MSD/T$_{max}$ problem). We classify the .DELTA.-unconstrained cases in the MSD/T$_{max}$ problem. We provide bounds to discern each case for the problem. It is also shown that the .DELTA.-unconstrained MSD/T$_{max}$ problem is equivalent to the unconstrained MSD problem and the tightly .DELTA.-constrained MSD/T$_{max}$ problem with n jobs and a maximum allowable tardiness .DELTA. can be converted into the constrained MSD problem with a common due date .DELTA. and n-1 jobs. Finally, the solution procedure for MSD/T$_{max}$ problem is provided. provided.

• 한국경영과학회지
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• 제25권2호
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• pp.47-57
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• 2000

In this paper we consider an n-job non-preemptive and identical parallel machine scheduling problem of minimizing the sum of earliness and tardiness with different release times and due dates. In the real world this problem is more realistic than the problems that release times equal to zero or due dates are common. The problem is proved to be NP-complete. Thus a heuristic is developed to solve this problem To illustrate its suitability a proposed heuristic is compared with a genetic algorithm for a large number of randomly generated test problems. Computational results show the effectiveness and efficiency of proposed heuristic. In summary the proposed heuristic provides good solutions than genetic algorithm when the problem size is large.

• 산업공학
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• 제12권1호
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• pp.121-131
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• 1999

In this article, a simulation model of a microwave oven assembly line is developed to identify system parameters to improve the system performances such as work-in-process inventories, production lead time, mean earliness, mean tardiness and in-time completion rate. System parameters investigated include dispatching rules, lot sizing, setup time reduction, demand increase, productivity improvement, production scheduling, hardware characteristics, etc. The model has been developed using SIMAN simulation language which has been demonstrated to be a powerful tool to simulate complex manufacturing systems. We have suggested the results obtained to improve the system performances of an existing production line.

• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.305-314
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• 2007

This paper considers single machine scheduling problems where the processing time of a job increases as a function of its position in the sequence. In this model, the later a given job is scheduled in the sequence, the longer its processing time. It is shown that the optimal schedule may be very different from that of the classical version of the problem. We introduce polynomial solutions for the makespan minimization problem, the sum of completion times minimization problem and the sum of earliness penalties minimization problem. For two resource constrained problems, based on the analysis of the problems, the optimal resource allocation methods are presented, respectively.

• 한국경영과학회지
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• 제24권3호
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• pp.73-82
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• 1999

In this paper, we address a single machine non-preemptive n-job scheduling problem to minimize the sum of earliness and tardiness with different release times and due dates. To solve the problem, we propose a genetic algorithm with new crossover and mutation operators to find the job sequencing. For the proposed genetic algorithm, the optimal pair of crossover and mutation rates is investigated. To illustrate the suitability of genetic algorithm, solutions of genetic algorithm are compared with solutions of exhaustive enumeration method in small size problems and tabu search method in large size problems. Computational results demonstrate that the proposed genetic algorithm provides the near-optimal job sequencing in the real world problem.

• 한국경영과학회지
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• 제23권1호
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• pp.29-41
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• 1998

This paper addresses the problem of scheduling a set of jobs with a common due data on a single machine. The objective is to minimize the sum of the earliness and tardiness of jobs subject to $T_{max}{\le}{\Delta}\;for{\Delta}{\ge}0$. Properties for the $MAD/T_{max}$ problem are found and the problem is shown to be NP-complete in the ordinary sense. According to the range of Δ, the problem can be solved in polynomial time. Also, some special cases where an optimal schedule is found in polynomial time are discussed.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.1071-1076
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• 2003

Evolutionary algorithm is recognized as a promising approach to solving multi-objective combinatorial optimization problems. When no preference information of decision makers is given, multi-objective optimization problems have been commonly used to search for diverse and good Pareto optimal solution. In this paper we propose a new multi-objective evolutionary algorithm based on competitive coevolutionary algorithm, and demonstrate the applicability of the algorithm. The proposed algorithm is designed to promote both population diversity and rapidity of convergence. To achieve this, the strategies of fitness evaluation and the operation of the Pareto set are developed. The algorithm is applied to job shop scheduling problems (JSPs). The JSPs have two objectives: minimizing makespan and minimizing earliness or tardiness. The proposed algorithm is compared with existing evolutionary algorithms in terms of solution quality and diversity. The experimental results reveal the effectiveness of our approach.

• 산업경영시스템학회지
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• 제19권39호
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• pp.293-299
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• 1996

The breakdown of machines lead to the lateness of parts and the change of schedules. Its treatment is very important problem in the shop floor control system. In this study, we present an algorithm minimize the lateness, earliness and change of schedule by controlling machining speed of available machines. Production time and production cost required to manufacture a piece of product are usually expressed as a unimodal convex fuction with respect to machining speed, and each has its minimal point at the minimum time speed or the minimum cost speed, and a speed range between these two speeds is called 'efficiency speed range'. Therefore, the algorithm determines the machining speed in the efficiency speed range. An example is demonstrated to explain the algorithm.