• 경영과학
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• 제17권1호
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• pp.41-54
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• 2000

in the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.

• 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.

• Industrial Engineering and Management Systems
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• 제7권3호
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• pp.204-213
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• 2008

Companies that produce capital goods need to schedule the production of products that have complex product structures with components that require many operations on different machines. A feasible schedule must satisfy operation and assembly precedence constraints. It is also important to avoid deadlock situations. In this paper a Genetic Algorithm (GA) has been developed that includes a new repair process that rectifies infeasible schedules that are produced during the evolution process. The algorithm was designed to minimise the combination of earliness and tardiness penalties and took into account finite capacity constraints. Three different sized problems were obtained from a collaborating capital goods company. A design of experimental approach was used to systematically identify that the best genetic operators and GA parameters for each size of 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.

• 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.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2004년도 추계학술대회
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• pp.409-416
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• 2004

동적 공급사슬망은 복잡하고 다양한 이해관계를 가진 기업들로 구성되어 있다. 다수의 구매자로부터 주문 의뢰가 동시다발적으로 발생하므로 하위 구성원들은 경쟁적 관계에 놓이게 된다. 그러므로 최적의 공급사슬구성을 위해서는 수평적 경쟁 관계를 고려하여 구성주체들간의 협력관계를 통해 이를 해결하여야 한다. 지금까지의 스케줄링 문제에서는 상위의 구성원이 하위 구성원들을 일방적으로 선택하는 의사결정이 이루어졌으나 본 문제에서는 구성원간의 협력관계에서 에이전트를 통한 다자간 협상을 통해 공급사슬 전체의 최적화를 구성하는 방법론을 제시한다. 본 협상방법론은 단일기계에서 상이한 납기일, 조기생산(earliness), 지연생산(tardiness)을 동시에 고려하였으며 전체 공급사슬의 평균절대편차(Mean Absolute Deviation)의 최소화를 목적으로 하고 있다. 본 협상방법론의 효과성을 증명하기 위해 분지한계법(Branch & Bound)과 비교하고, 알고리즘 구현을 통해 구매자 협상방법론의 최적화 여부를 실험을 통해 증명하였다.

• 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.

• Industrial Engineering and Management Systems
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• 제14권4호
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• pp.401-412
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• 2015

In this paper, we present a modeling approach to production planning for an actual production line and a heuristic method. We also illustrate the successful implementation of the proposed method on the production line. A heuristic algorithm called the push-back algorithm was designed for a single machine earliness/tardiness production planning with distinct due date. It was developed by combining a minimum slack time rule and shortest processing time rule with a push-back procedure. The results of a numerical experiment on the heuristic's performance are presented in comparison with the results of IBM ILOG CPLEX. The proposed algorithm was applied to an actual case of production planning at Woongjin Chemical, a leading manufacturer of filter products in South Korea. The seven-month execution of our algorithm led to a 24.5% decrease in the company's inventory level, thus demonstrating its practicality and effectiveness.

• 한국빅데이터학회지
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• 제5권1호
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• pp.189-195
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• 2020

본 논문은 딥러닝을 위한분산학습에서학습속도를 저하시키는 stale 문제를 최소화하기 위한 방법으로 데이터 시퀀싱을 제안하였다. 이데이터 시퀀싱 문제는일반 납기를 갖는 단일 공정 하에서 일찍 혹은 늦음 정도의 총합을 최소화 하는 스케줄링 문제로 모델링할 수 있다. 만약 최적해에서 크기가 작은 작업과 큰 작업의 순서가 미리 알려져 있다면, 이 스케줄링 문제가 효율적으로 풀린다는 것을 보였다.