• Management Science and Financial Engineering
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• v.20 no.2
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• pp.33-37
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• 2014

A flow shop scheduling problem involves scheduling jobs on multiple machines in series in order to optimize a given criterion. The flow time of a job is the amount of time the job spent before its completion and the stretch of the job is the ratio of its flow time to its processing time. In this paper, a hybrid genetic algorithm (HGA) approach is proposed for minimizing the total stretch in flow shop scheduling. HGA adopts the idea of seed selection and development in order to reduce the chance of premature convergence that may cause the loss of search power. The performance of HGA is compared with that of genetic algorithms (GAs).

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.17-23
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• 2008

In this research article, scheduling a casting sequence in a job-shop type foundry involving a variety of casts made of an identical alloy but with different shapes and II weights, has been investigated. The objective is to produce the assigned mixed orders satisfying due dates and obtaining the highest ingot efficiency simultaneously. Implementing simple integer programming instead of complicated genetic algorithms accompanying rigorous calculations proves that it can provide a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Enhancing the ingot efficiency under the constraint of discrete ingot sizes is accomplished by using a simple and intelligible algorithm in a standard integer programming. Employing this simple methodology, a job-shop type foundry is able to maximize the furnace utilization and minimize ingot waste.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.156-166
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• 1995

Job shop scheduling problem is a complex system and an NP-hard problem. Thus it is natural to look for heuristic method. We consider the multi-part production scheduling problem for quality level in a job shop scheduling under the existence of alternative routings. The problem is more complex if the processing time is imprecision. It requires suitable method to deal with imprecision. Fuzzy set theory can be useful in modeling and solving scheduling problems with uncertain processing times. Li-Lee fuzzy number comparison method will be used to compare processing times that evaluated under fuzziness. This study presents heuristic method for quality level in bottleneck-based job shop scheduling under fuzzy environment. On the basis of the proposed method, an example is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.517-522
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• 2005

This paper addresses scheduling heuristics for an assembly job-shop that includes at least an assembly process throughout its processes. The assembly job shop has certain characteristics not only considering the precedence relationship between the processes but also considering the processing progress between the parts. In addition, it probably presents a different processing time for the same product according to the order of processes and the point of workable time, due to the difference in the availability of equipments. The paper proposes several priority-based dispatching rules that consider these characteristics of the assembly job-shop, aiming to minimize the total tardiness of products in the shop floor. Computational tests showed that job due date based priority rules significantly outperform existing priority rules in terms of total tardiness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.140-146
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• 2005

This study presents the new dispatching rules of job shop scheduling with auxiliary resource constraint to improve the schedule performance measures related to completion time and due dates. The proposed dispatching rules consider the information of total work remaining and machine utilization to decrease mean flowtime and mean tardiness. The results of computer experiments show that those schedule performances are significantly improved by using the new dispatching rules. The results provide guidance for the researchers and practitioners of auxiliary resource constrained job shop scheduling to decrease mean flowtime and mean tardiness.

• Korean Management Science Review
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• v.9 no.1
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• pp.119-137
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• 1992

A two phase heuristic algorithm has been developed for the resolution of resource conflicts in a single project scheduling problem. Phase 1 of the algorithm generates a feasible schedule by repairing resource conflicts. Phase 2 finds local improvements in the schedule found in phase 1. Then, the algorithm has been applied to multi project and job shop scheduling. Computational results are compared with those of dispatching procedures. Index Terms-disjunctive constraints, heuristic algorithm, project scheduling, job-shop scheduling.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.429-434
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• 2002

For companies assembling end products from sub assemblies or components, MRP (Material Requirement Planning) logic is frequently used to synchronize and pace the production activities for the required parts. However, in MRP, the planning of operational-level activities is left to short term scheduling. So, we need a good scheduling algorithm to generate feasible schedules taking into account shop floor characteristics and multi-level job structures used in MRP. In this paper, we present a GA (Genetic Algorithm) solution for this complex scheduling problem based on a new gene to reflect the machine assignment, operation sequences and the levels of the operations relative to final operation. The relative operation level is the control parameter that paces the completion timing of the components belonging to the same branch in the multi-level job hierarchy. In order to revise the fixed relative level which solutions are confined to, we apply large step transition in the first step and GA in the second step. We compare the genetic algorithm and 2-phase optimization with several dispatching rules in terms of tardiness for about forty modified standard job-shop problem instances.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.99-102
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• 2000

전통적인 job shop 일정계획문제는 NP_hard 문제로 조합최적화 문제이다 일반적인 가정은 job이 방문하는 기계들의 경로가 고정되어 있다는 것이다. 경로 유연성을 가지는 job shop 일정계획문제는 job이 방문하는 기계들의 경로가 고정되어져 있지 않다는 것이다. 이러한 경우에 전통적인 job shop 문제를 복잡하게 만든다. 경로 유연성을 가지는 job shop 문제도 NP-hard 문제이다. 그러므로 휴레스틱이나 AI 기법들을 사용하는 하는 것이 불가피하게 되었다. 유전 알고리즘은 매우 복잡한 조합 최적화문제인 job shop 일정계획문제에 적용되어지고 있다. 이 논문은 최대완료시간(makespan)으로 경로 유연성을 가지는 job shop 일정계획문제를 풀기 위한 유전 알고리즘을 제시하고자 한다. 먼저 경로 유연성을 가지는 job shop 일정계획문제에 대한 정의를 내리고 유전 알고리즘을 구축하기 위한 첫 단계로 유전적 표현 즉, 개체 표현방법에 대해 설명하고 유전 연산자의 소개 그리고 알고리즘 재생과정을 제시하고 수치실험을 통해 알고리즘이 양질의 일정계획을 찾을 수 있다는 것을 보이고자 한다.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.125-125
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• 1991

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.