• Korean Management Science Review
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• v.33 no.1
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• pp.89-99
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• 2016

A scheduled airlift is the most critical part of the air transportation operations in ROK Air Force. The military cargo-plane routing problem is a PDPLS (pickup and delivery problem in which load splits and node revisits are allowed). The cargo which is transported by a military cargo-plane is measured in pallet. The efficiency of pallet needs to be considered with respect to its volume and weight. There are some guidelines about orders of priorities and regulations in the military air transportation. However, there are no methodologies which can raise the efficiency of flight scheduling using Operations Research (OR) theories. This research proposes the effective computing methodology and the related heuristic algorithms that can maximize the effectiveness of the path routing model.

• Korean Management Science Review
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• v.30 no.1
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• pp.15-24
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• 2013

We consider the single machine scheduling problem with a rate-modifying activity and time-dependent deterioration after the activity. The class of scheduling problems with rate-modifying activities and the class of scheduling problems with time-dependent processing times have been studied independently. However, the integration of these classes is motivated by human operators of tasks who has fatigue while carrying out the operation of a series of tasks. This situation is also applicable to machines that experience performance degradation over time due to mal-position or mal-alignment of jobs, abrasion of tools, and scraps of operations, etc. In this study, the integration of the two classes of scheduling problems is considered. We present a mathematical model to determine job-sequence and a position of a rate-modifying activity for the integration problem. Since the model is difficult to solve as the size of real problem being very large, we propose genetic algorithms. The performance of the algorithms are compared with optimal solutions with various problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.111-120
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• 2017

This paper proposes an improved standard genetic algorithm (GA) of making a near optimal schedule for integrated process planning and scheduling problem (IPPS) considering tool flexibility and tool related constraints. Process planning involves the selection of operations and the allocation of resources. Scheduling, meanwhile, determines the sequence order in which operations are executed on each machine. Due to the high degree of complexity, traditionally, a sequential approach has been preferred, which determines process planning firstly and then performs scheduling independently based on the results. The two sub-problems, however, are complicatedly interrelated to each other, so the IPPS tend to solve the two problems simultaneously. Although many studies for IPPS have been conducted in the past, tool flexibility and capacity constraints are rarely considered. Various meta-heuristics, especially GA, have been applied for IPPS, but the performance is yet satisfactory. To improve solution quality against computation time in GA, we adopted three methods. First, we used a random circular queue during generation of an initial population. It can provide sufficient diversity of individuals at the beginning of GA. Second, we adopted an inferior selection to choose the parents for the crossover and mutation operations. It helps to maintain exploitation capability throughout the evolution process. Third, we employed a modification of the hybrid scheduling algorithm to decode the chromosome of the individual into a schedule, which can generate an active and non-delay schedule. The experimental results show that our proposed algorithm is superior to the current best evolutionary algorithms at most benchmark problems.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.93-99
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• 1997

Most of the past studies on FMS scheduling problems may be classified into two classes, namely off-line scheduling and on-line scheduling approach. The off-line scheduling methods are used mostly for FMS planning purposes and may not be useful real time control of FMSs, because it generates solutions only after a relatively long period of time. The on-line scheduling methods are used extensively for dynamic real-time control of FMSs although the performance of on-line scheduling algorithms tends vary dramatically depending on various configurations of FMS. Current study is about finding a better on-line scheduling rules for FMS operations. In this study, we propose a method to create priority functions that can be used in setting relative priorities among jobs or machines in on-line scheduling. The priority functions reflect the configuration of FMS and the user-defined objective functions. The priority functions are generated from diverse dispatching rules which may be considered a special priority functions by themselves, and used to determine the order of processing and transporting parts. Overall system of our work consists of two modules, the Priority Function Evolution Module (PFEM) and the FMS Simulation Module (FMSSM). The PFEM generates new priority functions using input variables from a terminal set and primitive functions from a function set by genetic programming. And the FMSSM evaluates each priority function by a simulation methodology. Based on these evaluated values, the PFEM creates new priority functions by using crossover, mutation operation and probabilistic selection. These processes are iteratively applied until the termination criteria are satisfied. We considered various configurations and objective functions of FMSs in our study, and we seek a workable solution rather than an optimum or near optimum solution in scheduling FMS operations in real time. To verify the viability of our approach, experimental results of our model on real FMS are included.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.193-206
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• 2005

This paper considers a new flow-shop scheduling problem where a different WIP (work-in-process) state has different weight on the duration time. For the two machine case, the recognition version is NP-Complete in the strong sense. Several special cases are solved by different polynomial time algorithms. Finally, we develop a heuristic and provide an upper-bound on relative error which is tight in limit.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.36-45
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• 1993

This paper presents a model and a heuristic procedure to design production planning and transportation scheduling systems of critical items, components and products on the basis of material requirement planning concept and transportation planning model. These systems are stemmed from a multi-site multi-product production company in a international economic zone. An example is provided to validate the heuristic procedure developed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.162-165
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• 1997

본 연구에서는 off-line 스케쥴링과 on-line 스케쥴링을 함께 고려하는 스케쥴링 메카니즘에 대해 설명하였다. 일반적으로 스케쥴링은 off-line 문제를 주로 다룬다. 그러나, off-line으로 생성된 스케쥴은 실시간으로 발생하는 여러 문제들(기계 고장, 긴급 주문등) 때문에 현실과 맞지 않게 되어 유용성이 떨어지는 경우가 자주 발생한다. 따라서 off-line 스케쥴링의 결과를 수행할때 위와 같은 문제가 발생할 경우, 스케쥴의 변화를 흡수하면서 off-line 스케쥴링의 결과를 최대한 유지할수 있는 on-line 스케쥴링에서 이 같은 스케쥴 실행시의 문제를 해결할 수 있도록 bidding 알고리즘을 사용하는 방법을 제시하였다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.298-301
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• 2001

In semiconductor manufacturing, wafer fabrication is the most complicated and important process, which is composed of several hundreds of process steps and several hundreds of machines involved. The productivity of the manufacturing mainly depends on how well they control balance of WIP flow to achieve maximal throughput under short manufacturing cycle time. In this paper mathematical formulation is suggested for the stepper scheduling, in which cycle time reduction and maximal production is achieved.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.177-198
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• 1994

We consider an algorithm for the Crew Scheduling Problem (CSP) based on the Transportation Problem approach. The main flows of the algorithm are arranged in three steps. First we propose a heuristic algorithm of the greedy principle to obtain an initial feasible solution. Secondary we present a method of formulating CSP into a Modified Transportation Problem format. Lastly the procedures of network search to get the optimal solution are presented. This algorithm can be applied to the general GSP and also to most combinatorial problems like the Vehicle Routing Problems. The computational results show that the large size CSP's could be tackled.