• 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 the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.75-88
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• 1996

This paper presents an efficient heuristic technique for minimizing the objectives related to tardiness such as total tardiness, maximum tardiness and root mean of tardiness in the job shop scheduling. The heuristic technique iteratively improves an active schedule through exploring the schedule's neighborrhood, using operation move methods. The move operatio is defined on an active chain of tardy jobs in the active schedule. To find the move operations which have a high probability of reducing tardiness, we develop move methods by exploiting the properties of active chains. Our technique is compared with the two existing heuristic techniques, that is, MEHA(Modified Exchange Heuristic Algorithm) and GSP(Global Scheduling Procedure) under the various environmental with the three levels of due date tightness and several sized problems. The experimental results show that the proposed technique outperforms the two exissting techiques in terms of solution quality and computation time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.165-171
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• 1993

The algorithm of Giffler and Thompson is modified for solving job shop scheduling problems related to the overlapping production The start-lag and stop-lag are also applied New priority rules for the overlapping production are proposed and the efficiency of them is compared with that of the classical priority rules.

• Management Science and Financial Engineering
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• v.9 no.2
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• pp.47-68
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• 2003

We consider the customer order scheduling problem with job capacity restriction where the number of jobs in the shop at the same time is fixed. In the customer order scheduling problem, each job is part of some batch (customer order) and the composition of the jobs (product) in the batch is pre-specified. The objective function is associated with the completion time of the batches instead of the completion time of the jobs. We first summarize the known results for the general customer order scheduling problems. Then, we establish some new properties for the problems with job capacity restriction. For the case of unit processing time with the objective of minimizing makespan, we develop a polynomial-time optimal procedure for the two machine case. For the same problem with a variation of no batch alternation, we also develop a polynomial-time optimal procedure. Then, we show that the problems with the objectives of minimizing makespan and minimizing average batch completion time become NP-hard when there exist arbitrary number of machines. Finally, We propose optimal solution procedures for some special cases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.25
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• pp.23-31
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• 1992

This paper is concerned with an n jobs one machine Job shop scheduling problems in which all jobs have a common due date and unequal penalties occur when a job is completed before or after due date. The objective is to determine an optimal sequence and the corresponding common due date that yield the global minimum value of a penalty function Then a sequence that minimize the penalty function globally is a V-shaped sequence Using the idea of linear equations and a LGP(Linear Goal Programming), this paper shows that LGP and MAD(Mean Absolute Deviation) are equivalent problems. Therefore an efficient algorithm that is developed for MAD problem holds for LGP problem and vice-versa. A numerical example to account for the algorithm is provided.

• The Journal of Information Systems
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• v.25 no.4
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• pp.105-119
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• 2016

Purpose The conventional solution methods for production scheduling problems typically focus on the active schedules, which result in short makespans. However, the active schedules are more difficult to generate than the semi active schedules. In other words, semi active schedule based search strategy may help to reduce the computational costs associated with production scheduling. In this context, this paper aims to compare the performances of active schedule based and semi active schedule based search methods for production scheduling problems. Design/methodology/approach Two decoding approaches, active schedule decoding and semi active schedule decoding, are introduced in this paper, and they are used to implement genetic algorithms for classical job shop scheduling problem. The permutation representation is adopted by the genetic algorithms, and the decoding approaches are used to obtain a feasible schedule from a sequence of given operations. Findings The semi active schedule based genetic algorithm requires slightly more iterations in order to find the optimal schedule, while its execution time is quite shorter than active schedule based genetic algorithm. Moreover, the operations of semi active schedule decoding is easy to understand and implement. Consequently, this paper concludes that semi active schedule based search methods also can be useful if effective search strategies are given.

• IE interfaces
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• v.12 no.4
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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.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.69-100
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• 2009

In this paper, we consider a relatively new two-machine flow shop scheduling problem where the unit time WIP cost increases as a job passes through various stages in the production process, and the objective is to minimize the total WIP (work-in-process) cost. Specifically, we study three special cases of the problem. First, we consider the problem where processing times on machine 1 are identical. Second, the problem with identical processing times on machine 2 is examined. The recognition version of the both problems is unary NP-complete (or NP-complete in strong sense). For each problem, we suggest two simple and intuitive heuristics and find the worst case bound on relative error. Third, we consider the problem where the processing time of a job on each machine is proportional to a base processing time. For this problem, we show that a known heuristic finds an optimal schedule.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.91-104
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• 1993

This paper is concerned with flow shop scheduling problems having the common due date. V-shape property is used for algorithms with early and tardy penalty cost. The objective of this paper is developing efficient heuristic scheduling algorithms for minimizing total penalty cost function and determining the optimal common due date. The between job delay and the work in process are considered for developing algorithms as penalty cost. Algorithms is simulated to analyze interrelated factors. A numerical example is given for illustrating the proposed algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.23
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• pp.65-70
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• 1991

This paper is concerned with a flow-shop scheduling problem for all jobs having the common due date using V-Shape penalty cost function for earliness and lateness. The objective of the paper is to develop an efficient heuristic scheduling algorithm for minimizing total penalty cost function and for determining the optimal common due date. In addition, the between-job-delay for two machines are considered for developing the algorithm. A numerical example is given for illustrating the proposed algorithm.