• 지능정보연구
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• 제13권3호
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• pp.47-61
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• 2007

기업 운영에서 SCM (Supply Chain Management)의 중요성이 인식되면서 공급, 생산, 분배 등의 기능들을 통합적으로 관리하는 새로운 접근법의 필요성이 커지고 있다. 이 접근법은 여러 다른 기능들의 의사결정 문제를 하나의 통합된 최적화 모델로 분석하는 방법이다. 특히 공급사슬의 통합적인 운영을 위해서는 이전의 확정적 방법론 보다는 보다 구매자와 공급자의 관계를 유연하게 통합해 줄 수 있는 방법론이 필요하다. SCM은 대규모 문제이고 또한 다양한 내외 요인에 의해 기존의 설정된 계획 내용이나 상황이 항시 동적으로 변경될 수 있기에, 이들 정보를 통합 계획에 반영될 수 있도록 하여야 한다. 본 연구에서는 SCM의 핵심이 되는 생산계획과 분배계획 문제들을 효율적으로 통합할 수 있는 유전 알고리즘 (Genetic Algorithm)을 제시하고, 유전 알고리즘을 기반으로 동적 SCM을 위한 멀티 에이전트 시스템을 구현한다. 한편 통합계획 문제에서 유전 알고리즘을 통해 100%에 근접하는 최적해를 구하였고, 통합계획으로 얻은 결과와 통합 계획을 하지 않은 경우의 결과 값에서 큰 차이를 확인 할 수 있었다.

• 산업공학
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• 제17권spc호
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• pp.20-27
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• 2004

A flexible assembly system (FAS) is a production system that assembles various parts with many constraints and manufacturing flexibilities. This paper presents a new method for efficiently solving the integrated process planning and scheduling in FAS. The two problems of FAS process planning and scheduling are tightly related with each other. However, in almost all the existing researches on FAS, the two problems have been considered separately. In this research, an endosymbiotic evolutionary algorithm is adopted as methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary algorithm to solving the integrated problem. Some evolutionary schemes are used in the algorithm to promote population diversity and search efficiency. The experimental results are reported.

• Journal of Information Technology Applications and Management
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• 제20권2호
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• pp.147-160
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• 2013

Today, the management environments of intelligence firm are changing the way of production planning and logistics management, and are changing the process of supply chain management system. This paper shows the development of information system software for intelligence enterprises is used in supply chain management for robot engineering industry. Specifically, supply chain management system in this paper has been developed to analyze the impact of multi plant and multi distribution environment, showing the process analysis and system development of hierarchical assembly manufacturing industry. In this paper we consider a production planning and distribution management system of intelligence firm in the supply chain. We focus on a capacitated production resource and distribution volume allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using a genetic algorithm to solve it efficiently. This method makes it possible for the population to reach the feasible approximate solution easily. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solution converge to the feasible approximate solution quickly.

• 대한산업공학회지
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• 제35권1호
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• pp.15-39
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• 2009

Advanced planning and scheduling (APS) refers to a manufacturing management process by which raw materials and production capacity are optimally allocated to meet demand. APS is especially well-suited to environments where simpler planning methods cannot adequately address complex trade-offs between competing priorities. However, most scheduling problems of APS in the real world face both inevitable constraints such as due date, capability, transportation cost, set up cost and available resources. In this survey paper, we address three crucial issues in APS, including basic scheduling model, job-shop scheduling (JSP), assembly line balancing (ALB) model, and integrated scheduling models for manufacturing and logistics. Several evolutionary algorithms which adapt to the problems are surveyed and proposed; some test instances based on the practical problems demonstrate the effectiveness and efficiency of evolutionary approaches.

• Industrial Engineering and Management Systems
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• 제11권4호
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2001년도 추계학술대회 논문집
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• pp.253-256
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• 2001

Today's rapid development in the computer and network technology makes the environment which enables the companies to consider their decisions on the wide point of view and enables the software vendors to make the software packages to help these decisions. To make these software packages, many algorithms should be developed. The production and distribution planning problem belongs to those problems that industry manufacturers daily face in organizing their overall production plan. However, this combinatorial optimization problem can not be solved optimally in a reasonable time when large instances are considered. This legitimates the search for heuristic techniques. As one of these heuristic techniques, genetic algorithm has been considered in many researches. A standard genetic algorithm is a problem solving method that apply the rules of reproduction, gene crossover, and mutation to these pseudo-organisms so those organisms can Pass beneficial and survival-enhancing traits to new generation. This standard genetic algorithm should not be applied to this problem directly because when we represent the chromosome of this problem, there may exist high epitasis between genes. So in this paper, we proposed the hybrid genetic algorithm which turns out to better result than standard genetic algorithms

• 한국국방경영분석학회지
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• 제24권2호
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• pp.162-169
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• 1998

This study presents an single machine scheduling algorithm minimize lateness of product by controlling machining speed. Generally, production scheduling uses the information of process planning. But the production scheduling algorithm has not considered the control of machining speed in its procedures. Therefore, the purpose of this study is to consider the machining speed in production scheduling algorithm for efficient production scheduling. Machining time and machining cost required to manufacture a piece of a product are expressed as a unimodal convex function with respect to machining speed, so it has minimal point at minimum time speed or the minimum cost speed. Therefore, because of considering the machining cost, the control of machining speed for the algorithm is executed between minimum speed and maximum speed. An example is demonstrated to explain the algorithm.

• 한국산업정보학회논문지
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• 제13권5호
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• pp.142-148
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• 2008

Facility Layout Planning is concerned with how to arrange facilities necessary for production in a given space. Its objective is often to minimize the total sum of all material flows multiplied by the distance among facilities. FLP belongs to NP complete problem; i.e., the number of possible layout solutions increases with the increase of the number of facilities. Thus, meta heuristics such as Genetic Algorithm (GA) and Simulated Annealing have been investigated to solve the FLP problems. However, one of the biggest problems which lie in the existing meta heuristics including GA is hard to find an appropriate combinations of parameters which result in optimal solutions for the specific problem. The Ant System algorithm with elitist and ranking strategies is used to solve the FLP problem as an another good alternative. Experimental results show that the AS algorithm is able to produce the same level of solution quality with less sensitive parameters selection comparing to the ones obtained by applying other existing meta heuristic algorithms.

• 품질경영학회지
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• 제22권1호
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• pp.188-204
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• 1994

Most of computer-aided process planning(CAPP) systems have been developed to automate the process planning function. In this paper, we describe an analytical model for a CAPP system in order to improve the performance of production system in flexible manufacturing systems(FMSs) for computer intergrated manufacturing(CIM) architecture. This paper proposes an optimal process planning that minimizes the load time by minimizing the cycle time and the number of workstations using Kang and Hahm's heuristic approach so as to improve the performance of production system under the batch production of discrete products. We also perform simulation using SIMAN language to campare the line utilization of each for various product types. The proposed algorithm can be implemented in existing FMSs for on-line control of product quantity using programmable logic controllers(PLC) and communication devices.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.621-626
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• 1989

An efficient algorithm for planning near-optimum trajectory of manipulators is proposed. The algorithm is divided into two stages. The first one is the optimization of time trajectory with given spatial path. And the second one is the optimization of the spatial path itself. To consider the second problem, the manipulator dynamics is represented using the path parameter "s", then a differential equation corresponding to the dynamics is solved as two point boundary value problem. In this procedure, the gradient method is used to calculate improved input torques.t torques.