• Korean Management Science Review
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• v.12 no.2
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• pp.77-87
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• 1995

In this paper we develop an efficient heuristic algorithm for the problem of scheduling n sequence-dependent jobs on a basic processor to minimize makespan. Efficient solution methods are already known for the sequence- independent case. But for the sequence-dependent case, this problem belongs to a set of strong NP-complete problems. We present a heuristic which is similar to shortest setup time heuristic but opportunity cost of setup time rather than shortest setup time is used for choosing next job. This heuristic algorithm has same computational complexity and worst case ratio as the shortest setup time heuristic. We used Wilcoxon signed rank test to show that our heuristic is superior to nearest setup time heuristic in term of average behavior.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.119-126
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• 1993

We study a manufacturing process that is quite common in semiconductor wafer fabrication of semiconductor chip production. A machine is used to process a job consisting of J wafers. Each job requires a setup, and the i$_{th}$ setup for a job is sucessful with probability P$_{i}$. The setup is prone to failure, which results in the loss of expensive wafers. Therefore, a tiral run is first conducted on a small batch. If the set up is successful, the test is passed and the balance of the job can be processed. If the setup is unsuccessful, the exposed wafers are lost to scrap and the mask is realigned. The process then repeats on the balance of the job. We call this as send-ahead policy and consider general policies in which the number of wafers that are sent shead depend on the cost of the raw wafer, the sequence of success probabilities, and the balance of the job. We model this process and determine the expected number of good wafers per job,the expected time to process a job, and the long run average throughput. An algorithm to minimize the cost per good wafer subject to a demand constraint is provided.d.d.

• 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 Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.532-541
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• 1997

This article derives an analytic solution to determine the optimal size of multiple noncontinuous process and storage units. The total cost to be minimized consists of the setup cost of noncontinuous processing units and the inventory holding cost of feedstock/product storages. A novel approach, which is called PSW(Periodic Square Wave) model, is applied to represent the material flow among non-continuous units and storages. PSW model presumes that the material flow between unit and storage is periodic square wave shaped. The resulting optimal unit size has similar characteristics with the classical economic lot sizing model such as EOQ(Economic Order Quantity) or EPQ(Economic Production Quantity) model in a sense that the unit size is determined as the balance between setup and inventory holding cost. However, the influence of inventory holding cost of PSW model is different from that of EOQ/EPQ model. EOQ/EPQ model includes only the product inventory holding cost but PSW model includes all inventory holding costs around the non-continuous unit with proportional contribution. PSW model is suitable for analyzing interlinked process-storage system. The optimal lot size of PSW model is smaller than that of EOQ/EPQ model. This is quitea remarkable result considering that the EOQ/EPQ model has been is widely used since last half century.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.27-41
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• 2005

This paper considers identical parallel machine scheduling problem. Each job has a processing time. due date. weight and family type. If a different type of job is followed by prior job. a family setup is incurred. A two phased heuristic is presented for minimizing the sum of weighted tardiness. In the first phase. using roiling horizon technique. group each job into same family and schedule each family. In the second phase. assign each job to machines using schedule obtained in the first phase. Extensive computational experiments and comparisons among other algorithms are carried out to show the efficiency of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.12
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• pp.41-49
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• 2004

Increase of internet users and new types of applied traffics, have led to demand for more bandwidth for each application. Hence, the amount of internet traffic has risen sharply and it has demanded to use limited resources, such as wavelength and bandwidth, more effectively. These kind of needs can be satisfied with OXC(Optical cross-connects) based on GMPLS that carry out IP packet switching and wavelength switching at the same time and Provide very wide bandwidth. In RSVP-TE signaling of GMPLS studied by IETF. every lambda router in core network should be able to convert wavelength. So, lots of wavelength converters and needed and building and managing cost is high. Another problem is that optimized traffic is limited. In this paper We suggest strengthened GMPLS RSVP-TE signaling algorithm for a better lightpath setup. When setup signaling is blocked suggested algorithm does not send PathErr message to Edge Router, but looks for nearest lambda router which can convert wavelength and carry out setup signaling from that node. Such algorithm can reduce the chance of blocked lightpath setup signaling and provide effective arrangement of lambda router in core network by calculating proper number of wavelength converter.

• IE interfaces
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• v.8 no.2
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• pp.151-159
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• 1995

Two-dimensional cutting stock problem is to find a waste-minimizing method of cutting a single rectangular plane into a number of smaller pieces of known dimensions. In practice, besides wastes, setup cost taken during adjusting is of an important concern. We suggest 2-phased guillotine cutting method as a solution to the problem which minimize wastes and setup costs. Also, in order to reduce the computing time we apply techniques of discretization, cutoff, median. Experimental results show good performance of our algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.79-88
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• 1989

This characteristics of process industries are high capital intensity, relatively long and sequence dependent setup times, and extremely limited capacity resources. The lot sizing, sequencing and limited capacity resources factors must he considered for production scheduling in these industries. This paper presents a mixed integer programming model for production scheduling. The economic trade offs between capacitated lot sizing flow shop scheduling and sequence dependent setup times also be compared with SMITH-DANIELS's model. As a results, it is shown that this paper has lower total cost, more efficient throughput than SMITH-DANIELS's model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.169-175
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• 2021

The lot sizing problem(LSP) is a hard problem that classified as non-deterministic(NP)-complete because of the polynomial-time optimal solution algorithm is unknown yet. The well-known W-W algorithm can be obtain the solution within polynomial-time, but this algorithm is a very complex, therefore the heuristic approximated S-M algorithm is suggested. This paper suggests O(n) linear-time complexity algorithm that can be find not the approximated but optimal solution. This algorithm determines the lot size Xt∗ in period t to the sum of the demands of interval [t,t+k], the period t+k is determined by the holding cost will not exceed setup cost of t+k period. As a result of various experimental data, this algorithm finds the optimal solution about whole data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.117-126
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• 2015

This paper is to analyze an integrated production and inventory model in a single-vendor multi-buyer supply chain. The vendor is defined as the manufacturer and the buyers as the retailers. The product that the manufacturer produces is supplied to the retailers with constant periodic time interval. The production rate of the manufacturer is constant for the time. The demand of the retailers is constant for the time. The cycle time of the vendor is defined as the elapsed time from the start of the production to the start of the next production, while the cycle times of the buyer as the elapsed time between the adjacent supply times from the vendor to the buyer. The cycle times of the vendor and the buyers that minimizes the total cost in a supply chain are analyzed. The cost factors are the production setup cost and the inventory holding cost of the manufacturer, the ordering cost and the inventory holding cost of the retailers. The cycle time of the vendor is investigated through the cycle time that satisfies economic production quantity with the production setup cost and the inventory holding cost of the manufacturer. An integrated production and inventory model is formulated, and an algorithm is developed. An numerical example is presented to explain the algorithm. The solution of the algorithm for the numerical examples is compared with that of genetic algorithm. Numerical example shows that the vendor and the buyers can save cost by integrated decision making.