• 산업경영시스템학회지
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• 제14권23호
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• pp.27-36
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• 1991

This paper considers scheduling a set of n-jobs on m-paraller identical processors in which all jobs have the common due date. The objective of the problem is to minimize the weighted mean absolute deviation of job completion times about such common due dates under the assumption that each job has a different weight. and to determine the optimal value of a common due date. We propose four heuristic solution methods based on several dominance conditions, and its solution procedure is illustrated with numerical examples. The Performance comparison is made among four heuristic scheduling procedures.

• 산업경영시스템학회지
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• 제19권39호
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• pp.275-284
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• 1996

It can be made a definition that scheduling is a imposition of machinery and equipment to perform a collection of tasks. Ultimately scheduling is an assessment of taking order for which would be perform. So it is called "sequencing" in other words. In a job shop scheduling, the main object is to making delivery in accordance with the due date and order form customer, not to producing lots of quantity with minimizing mean flow time in a given time. Actually, in a company, they concentrate more in the delivery than minimizing the mean flow time. Therefore this paper suggest a new priority dispatching rule under consideration as below in a n/m job shop scheduling problem with due date. 1. handling/transportation time, 2. the size of customer order With this algorithm, we can make a scheduling for minimizing the tardiness of delivery which satisfy a goal of production.roduction.

• 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.

• 산업경영시스템학회지
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• 제32권3호
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• pp.110-117
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• 2009

This paper introduces a case study for efficient generation of production schedules in a tube manufacturing system. The considered scheduling problem consists of two sub problems : lot sizing for a job and Job sequencing. Since these problems require simulation optimization in which the performance measures are obtained by simulation execution, the trade-off between solution quality and computation time is an important issue. In this study, the optimal lot size for every product type is determined from simulation experiments. Then, target production quantity for each product type is transformed to several jobs such that a Job consists of determined lot size. To obtain the good solution for a Job sequence in a reasonable time, a number of alternatives are generated from heuristic rules developed by intuition and analysis of the considered system, and a job sequence is selected from simulation experiments.

• 한국항해항만학회지
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• 제29권2호
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• pp.141-146
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• 2005

For a long time, genetic algorithms have been recognized as a new method to solve difficult and complex problems and the performance of genetic algorithms depends on genetic operators, especially crossover operator. Various problems like the traveling salesman problem, the transportation problem or the job shop problem, in logistics engineering can be modeled as a sequencing problem This paper proposes modified genetic crossover operators to be used at various sequencing problems and uses the traveling salesman problem to be applied to a real world problem like the delivery problem and the vehicle routing problem as a benchmark problem Because the proposed operators use parental information as well as network information, they could show better efficiency in performance and computation time than conventional operators.

• Journal of Communications and Networks
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• 제6권2호
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• pp.147-155
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• 2004

In this paper, we propose an efficient sequencing technique, namely minimum Row time scheduling (MFTS), to manage variable-Iength message transmissions for single-hop passive starcoupled WDM optical networks. By considering not only the message length but also the state of the receivers and the tuning latency, the proposed protocol can reduce the average delay of the network greatly. This paper also introduces a new channel assignment technique latency minimizing scheduling (LMS), which aims to reduce the scheduling latency. We evaluate the proposed algorithm, using extensive discrete-event simulations, by comparing its performance with shortest job first (SJF) algorithm. We find that significant improvement in average delay could be achieved by MFTS algorithm. By combining the proposed message sequencing technique with the channel selection technique, the performance of the optical network could be further improved.

• 한국경영과학회지
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• 제4권1호
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• pp.69-77
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• 1979

A single machine stochastic scheduling problem is considered. Associated with each job is its random processing time and random deferral cost. The criterion is to order the jobs so as to minimize the sum of the deferral costs. The expected sum of the deferral costs is theroretically derived under the stochastic situation for each of several scheduling decision rules which are well known for the deterministic environment. It is also shown that certain stochastic problems can be reduced to equivalent deterministic problems. Two examples are illustrated to show the expected total deferral costs.

• 산업공학
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• 제13권3호
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• pp.512-520
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• 2000

An integrated process planning and scheduling model considering outsourcing in manufacturing supply chain is proposed in this paper. The process planning and scheduling considering outsourcing are actually interrelated and should be solved simultaneously. The proposed model considers the alternative process plans for job types, precedence constraints of job operations, due date of production, transportation time and production information for outsourcing. The integrated states include:(1) Operations sequencing, (2) Machine selection, (3) Scheduling with outsourcing under the due date. To solve the model, a heuristic approach based on genetic algorithm(GA) is developed. The proposed approach minimizes the makespan considering outsourcing and shows the best operation-sequences and schedule of all jobs.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.617-620
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• 2000

In this paper, we show an application of constraint logic programming to the operation scheduling on machines in a job shop. Constraint logic programming is a new genre of programming technique combining the declarative aspect of logic programming with the efficiency of constraint manipulation and solving mechanisms. Due to the latter feature, combinatorial search problems like scheduling may be resolved efficiently. In this study, the jobs that consist of a set of related operations are supposed to be constrained by precedence and resource availability. We also explore how the constraint solving mechanisms can be defined over a scheduling domain. Thus the scheduling approach presented here has two benefits: the flexibility that can be expected from an artificial intelligence tool by simplifying greatly the problem; and the efficiency that stems from the capability of constraint logic programming to manipulate constraints to prune the search space in an a priori manner.

• 산업공학
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• 제14권4호
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• pp.385-393
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• 2001

In this paper, a scheme of scheduling a bottleneck operation is presented for production planning of make-to-order. We focus on the problem of capacity-dependent processing time in which processing time of the bottleneck operation is not fixed, but varies with job sequence or equipment capacity. For this, a genetic algorithm is applied for job sequencing with an objective function of mean square of weighted deviation. An experimental study is implemented in power transformer plant and results are compared with those of the EDD rule. It shows that the genetic algorithm is relatively good for most cases.