• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.141-157
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• 2013

In this paper, we consider the minimization of the total weighted earliness-tardiness penalty of jobs, regarding the partial precedences between jobs. We present an optimal scheduling algorithm in O(n(n+m log m)) where n is the number of jobs and m is the number of partial precedences. In the algorithm, the optimal schedule is constructed iteratively by considering each group of contiguous jobs as a block that is represented by a tree.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.1-22
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• 2005

This paper presents new scheduling heuristics, namely Mean Progressive Weighted Tardiness Estimator (MPWT) Heuristic Method and modified priority rules with sequence-dependent setup times consideration. These are designed to solve job shop scheduling problems with new performance measures - progressive weighted tardiness penalties. More realistic constraints, which are inter-machine overlapping sequence-dependent setup times, are considered. In real production environments, inter-machine overlapping sequence-dependent setups are significant. Therefore, modified scheduling generation algorithms of active and nondelay schedules for job shop problems with inter-machine overlapping sequence-dependent setup times are proposed in this paper. In addition, new customer-based measures of performance, which are total earliness and progressive weighted tardiness, and total progressive weighted tardiness, are proposed. The objective of the first experiment is to compare the proposed priority rules with the consideration of sequence-dependent setup times and the standard priority rules without setup times consideration. The results indicate that the proposed priority rules with setup times consideration are superior to the standard priority rules without the consideration of setup times. From the second experiment and the third experiment to compare the proposed MPWT heuristic approach with the efficient priority rules with setup times consideration, the MPWT heuristic method is significantly superior to the Batched Apparent Tardiness Cost with Sequence-dependent Setups (BATCS) rule, and other priority rules based on total earliness and progressive weighted tardiness, and total earliness and tardiness.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.115-130
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• 1995

This paper considers a single machine nonpreemptive scheduling problem with a given common due date. In the problem, the optimal job sequence is sought to minimize the sum of earliness/tardiness and flow time measures in the situation where all jobs are available at time zero, and weights per unit length of earliness/tardiness and flow time are V and W, respectively. Some dominant solution properties are characterized to deriva both an optimal starting time for an arbitrary sequence and sequence improvement rules. The optimal schedule is found to the case W .geq. V/. By the way, it is difficult to find the optimal schedule for the case W < V. Therefore, the derived properties are put on together to construct a heuristic solution algorithm for the case W < V, and its effectiveness is rated at the mean relative error of about 3% on randomly generated numerical problems.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.192-203
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• 1999

This paper deals with the order release problem for minimizing weighted earliness and tardiness as well as Work In Process (WIP) in dynamic job shop environments. A newly designed hierarchical order release mechanism is developed for efficient real-time control of the earliness/tardiness and WIP. The hierarchical order release mechanism consists of the order release plan and the order release control which is composed of two procedures. The experimental results show that the proposed order release mechanism is superior to other four order release mechanisms under overall simulation conditions of utilization rate, due-date allowances, and earliness/tardiness cost structures. In addition, the difference of total cost among the four dispatching rules is much more reduced in the proposed order release mechanism than in other release mechanisms.

• IE interfaces
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• v.10 no.2
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• pp.57-67
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• 1997

This paper is a report of a simulation study that investigates a dynamic approach to scheduling jobs in a conventional shop floor, especially in an assemoly-type welding process. We consider both JIT arrival and JIT delivery. Various dispatching rules are tested for the following performance measures; mean flow time, rate of tardy jobs, mean tardiness, sum of mean tardiness and mean earliness. The results indicate that SPT rule is the best for the mean flow time. MSLACK that we suggest in this paper, is the best for the mean tardiness and the sum of mean tardiness and mean earliness. However, it is not clear that which rule is the best for the rate of tardy jobs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.21-28
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• 2008

본 연구는 반도체 제조공정에서 사용되는 단일 Burn-In oven에서의 Total weighted earliness와 Tardiness를 최소화하기 위한 생산 스케줄링을 결정하는 문제를 다룬다. 본 연구에서는 모든 작업은 상시에 시작가능하고 각각은 서로 다른 가중치를 가지고 있다고 가정하였다. 일반적으로 단일 Burn-In oven은 다양한 작업들이 동시에 가능한 Batch processing 기계이다. 따라서 다양한 작업들로 구성된 하나의 Batch의 Processing time은 그 Batch 내에 있는 가장 긴 Processing time을 가지는 작업에 의해 결정된다. 본 연구에서 Batch size는 미리 결정되지 않은 상황이라고 가정한 후, 최적의 Batch 개수와 작업의 순서를 결정하기 위해 유전자 알고리즘을 적용하였다. 수리적 예제를 통해서 다양한 접근방법의 성능들을 비교한 결과, 유전자 알고리즘이 Total weighted earliness와 Tardiness를 최소화하는데 가장 뛰어난 성능을 가지고 있음을 알 수 있다.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.51-62
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• 2013

This paper considers a single machine rescheduling problem whose original (efficiency related) objective is minimizing makespan. We assume that disruptions such as order cancelations and newly arrived orders occur after the initial scheduling, and we reschedule this disrupted schedule with the objective of minimizing a disruption related objective while preserving the original objective. The disruption related objective measures the impact of the disruptions as difference of completion times in the remaining (uncanceled) jobs before and after the disruptions. The artificial due dates for the remaining jobs are set to completion times in the original schedule while newly arrived jobs do not have due dates. Then, the objective of the rescheduling is minimizing the maximum earliness without tardiness. In order to preserve the optimality of the original objective, we assume that no-idle time and no tardiness are allowed while rescheduling. We first define this new problem and prove that the general version of the problem is unary NP-complete. Then, we develop three simple but intuitive heuristics. For each of the three heuristics, we find a tight bound on the measure called modified z-approximation ratio. The best theoretical bound is found to be 0.5 - ${\varepsilon}$ for some ${\varepsilon}$ > 0, and it implies that the solution value of the best heuristic is at most around a half of the worst possible solution value. Finally, we empirically evaluate the heuristics and demonstrate that the two best heuristics perform much better than the other one.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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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.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.1-12
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• 2012

In this paper, we report a case study on the common due-date assignment and scheduling problem in a paper remanufacturing system that produces corrugated cardboards using collected waste papers for a given set of orders under the make-to-order (MTO) environment. Since the system produces corrugated cardboards in an integrated process and has sequence-dependent setups, the problem considered here can be regarded as common due-date assignment and sequencing on a single machine with sequence-dependent setup times. The objective is to minimize the sum of the penalties associated with due-date assignment, earliness, and tardiness. In the study, the earliness and tardiness penalties were obtained from inventory holding and backorder costs, respectively. To solve the problem, we adopted two types of algorithms: (a) branch and bound algorithm that gives the optimal solutions; and (b) heuristic algorithms. Computational experiments were done on the data generated from the case and the results show that both types of algorithms work well for the case data. In particular, the branch and bound algorithm gave the optimal solutions quickly. However, it is recommended to use the heuristic algorithms for large-sized instances, especially when the solution time is very critical.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.699-708
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• 1997

Production control is usually composed of due-dote assignment, production input control, and priority dispatching rule. A production input control(PIC) is mainly to control the WIP level on the shop floor. On the other hand, a priority dispatching rule(PDR) is mainly to control the tardiness/earliness of on order and number of tardy jobs. Therefore, if we select a particular PIC which can control only a particular performance measure(i.e., tardiness), it may cause worsening other performance measure(i.e., WIP level, shopfloor time, etc.) This newly developed production input control, DRD(Dual Release-Dates), is mainly designed to control the WIP level on the shop floor by employing two different release-dates of an order(earliest release. date and latest release-date and the release condition (relationship between the current WIP level and the pre-defined maximum WIP level) while trying to meet the due-date of the order.