• Korean Management Science Review
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• v.16 no.2
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• pp.125-135
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• 1999

This paper presents a framework for the hierarchical PPC(Production Planning and Control) in make-to-order environment with job shop. The characteristics of the environment are described as : 1) project with non-repetitive and individual production, 2) short delivery date, 3) process layout with large scales manufacturing. 4) job shops. The PPC in a make-to-order typically are organized along hierarchical fashions. A model is proposed for the hierarchical job shop scheduling based on new concepts of production system, work and worker organization. Then, a new integrated hierarchical framework is also developed for the PPC based on concepts of the proposed job shops scheduling model. Finally, the proposed framework has been implemented in the Electric Motor Manufacturing and the results showed good performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.59
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• pp.11-20
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• 2000

The Job Shop Scheduling Problem(JSSP) is one of the most general and difficult of all traditional scheduling problems. The goal of this research is to develop an efficient scheduling method based on single genetic algorithm(SGA) and parallel genetic algorithm (PGA) to address JSSP. In this scheduling method, new genetic operator, generating method of initial population are developed and island model PGA are proposed. The scheduling method based on PGA are tested on standard benchmark JSSP. The results were compared with SGA and another GA-based scheduling method. The PGA search the better solution or improves average of solution in benchmark JSSP. Compared to traditional GA, the proposed approach yields significant improvement at a solution.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.348-352
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• 2000

Intelligent agents represent parts and manufacturing resources, which cooperate, negotiate, and compete with each other. The negotiation between agents is in general based on the Contract-Net-Protocol. This paper describes a new approach to negotiation-based job shop scheduling. The proposed method includes multi-negotiation strategy as well as single-negotiation. A case study showing the comparison of various negotiation strategies is also given.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.11-18
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• 2016

This paper considers a scheduling problem in a flexible job shop with a reconfigurable manufacturing cell. The flexible job shop has both operation and routing flexibilities, which can be represented in the form of a multiple process plan, i.e. each part can be processed through alternative operations, each of which can be processed on alternative machines. The scheduling problem has three decision variables: (a) selecting operation/machine pairs for each part; (b) sequencing of parts to be fed into the reconfigurable manufacturing cell; and (c) sequencing of the parts assigned to each machine. Due to the reconfigurable manufacturing cell's ability of adjusting the capacity, functionality and flexibility to the desired levels, the priority scheduling approach is proposed in which the three decisions are made at the same time by combining operation/machine selection rules, input sequencing rules and part sequencing rules. To show the performances of various rule combinations, simulation experiments were done on various instances generated randomly using the experiences of the manufacturing experts, and the results are reported for the objectives of minimizing makespan, mean flow time and mean tardiness, respectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.105-114
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• 2000

Job Shop Problem which consists of the m different machines and n jobs is a NP-hard problem of the combinatorial optimization. Each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. Each machine can process at most one operation at a time. The purpose of this paper is to develop the heuristic method to solve large scale scheduling problem using Constraint Satisfaction Problem method and Simulated Annealing. The proposed heuristic method consists of the search algorithm and optimization algorithm. The search algorithm is to find the solution in the solution space using CSP concept such as backtracking and domain reduction. The optimization algorithm is to search the optimal solution using SA. This method is applied to MT06, MT10 and MT20 Job Shop Problem, and compared with other heuristic method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.187-192
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• 2014

Lot-streaming is the process of splitting a job (lot) into sublots to allow the overlapping of operations between successive machines in a multi-stage production system. A new genetic algorithm (NGA) is proposed for an n-job, m-machine, lot-streaming flow shop scheduling problem with equal-size sublots in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. NGA replaces the selection and mating operators of genetic algorithms (GAs) by marriage and pregnancy operators and incorporates the idea of inter-chromosomal dominance and individuals' similarities. Extensive computational experiments for medium to large-scale lot-streaming flow-shop scheduling problems have been conducted to compare the performance of NGA with that of GA.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.161-170
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• 1999

This paper evaluates forty different dispatching rules with respect to twenty different performance measures of job shop scheduling under seven levels of workload imbalance. Computer simulation is used as a tool to determine rankings of the dispatching rules for a given workload imbalance. The experiments results show rankings of dispatching rules are different in the job shop with unbalanced machine workloads. As variations of workload imbalance increase from 7% to 78%, the performance of dispatching rules is gradually deteriorated in measure related to completion time and due date. These results guide scheduling practitioners not only to choosing dispatching rules but also to developing the model of facility investment for workload balance, when there are different levels of workload imbalance.

• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.71-82
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• 1997

이 연구의 모형은, 자원(기계, 인력), 주문(작업)의 의미를 확정한 "일반화된 job-shop"이다. 이 모형의 제약조건을 파악한 후, 불확정 제약조건의 표현과 추론방법을 연구하였으며, 이를 위하여 일정계획 수립 기능들을 모듈화하였다. 불확정제약조건에 따라 모듈들을 선택적으로 사용하기 위한 추론 과정은, 먼저, 납기만족이 우선이며 제약만족(CSP) 일정계획 모듈을 사용하고 그렇지 않으면 디스패칭 모듈을 사용한다. 그리하여, 납기, 작업시간의 불확정성과 자원의 변동, 새 주문의 추가, 일정계획 목표의 변경등을 반영하는 일정계획 수립방법을 제시하였다. 이 논문은 제약만족 일정계획과 디스패칭 일정계획을 하나의 틀에서 함께 사용함으로써, 일정계획 목표의 변경이나 제조환경이 변화에 대처할 수 있음을 보인다.수 있음을 보인다.

• Korean Management Science Review
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• v.10 no.2
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• pp.61-77
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• 1993

This paper involves a study of developing the production scheduling system in a general job shop type mechanical factory. We consider realistic situations in the job-shop environments, such as alternative machines for operation, the new kinds of processes, the machining center with the plural pallet, the operational situation of each machine during the scheduling period, occurings of urgent orders and machine breakdowns. We also propose the methodology of re-schedule. It is very fast and acceptable for real time production control system. These all functions are implemented on IBM PC and program source is written in PASCAL language.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.642-647
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• 2014

In this paper, a hybrid genetic algorithm (HGA) approach is proposed for an n-job, m-machine flow shop scheduling problem with limited capacity buffers with blocking in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. HGA adopts the idea of seed selection and development in order to improve the exploitation and exploration power of genetic algorithms (GAs). Extensive computational experiments have been conducted to compare the performance of HGA with that of GA.