• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.125-132
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• 1991

This paper is concerned with the flow shop scheduling problems considering different weighted penalty costs for earliness and lateness, and a common due date. The objective of the paper is to develop an efficient heuristic scheduling algorithm for minimizing total penalty costs and for determining the optimal common due date. The positional weight index and, the product sum method are used. A numerical example is given for illustrating the proposed algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.9 no.1
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• pp.33-43
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• 1983

This paper develops a general methodology for evaluating inspection (mainly, safety inspection) policies, standard and regulations in a complex system with lots of components. Based on practically available data, this methodology enable planners and regulators to estimate the costs and effectiveness of different inspection policies when applied under different system working conditions. As main tools, the concepts of detection probability and earliness of detection are developed in this paper.

• Korean Journal of Breeding Science
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• v.42 no.3
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• pp.231-235
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• 2010

'Jopung' (Avena sativa L.), a winter oat for forage use, was developed by the breeding team at the Department of Rice and Winter Cereal Crop, NICS, RDA in 2009. It was derived from an original cross between the $F_1$ hybrid of 'Early80' and 'PA202-210-S' and 'Walken' in 1999. Subsequent generations followed by the cross were handled in bulk and pedigree selection programs at Suwon and Yeoncheon, respectively. A line, 'SO99006-B-YB-29-Y1', was selected for earliness and good agronomic characteristics and designated as a line name of 'Gwiri65'. The line 'Gwiri65' was subsequently evaluated for earliness and forage yield in four different locations, Yesan, Iksan, Kimjae, and Jeju, from 2007 to 2009 and finally named as 'Jopung'. Over 3 years, the average forage dry matter yield of cultivar 'Jopung' harvested at milk-ripe stage was $17.3MT\;ha^{-1}$, compared with $13.6MT\;ha^{-1}$ of check cultivar 'Swan'. The silage quality of 'Jopung' was superior to the check cultivar 'Swan' in crude protein content, and was similar to the check cultivar in percent total digestible nutrients (TDN). Cultivar 'Jopung' is suitable primarily for winter planting in the southern regions of Korean peninsula.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.81-92
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• 1990

This paper considers a scheduling of a set of jobs on single and multiple processors, when all jobs have a common due date and earliness and lateness are penalized at different cost rates. The objective is to determine the optimal value of a common due date and an optimal scheduling to minimize a total penalty function. It is also shown that a schedule having minimum weighted completion time variances must be V-shaped. For identical processors, a polynomial scheduling algorithm with the secondary objectives of minimizing makespan and machine occupancy is developed and a numerical example is presented.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.401-412
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• 2015

In this paper, we present a modeling approach to production planning for an actual production line and a heuristic method. We also illustrate the successful implementation of the proposed method on the production line. A heuristic algorithm called the push-back algorithm was designed for a single machine earliness/tardiness production planning with distinct due date. It was developed by combining a minimum slack time rule and shortest processing time rule with a push-back procedure. The results of a numerical experiment on the heuristic's performance are presented in comparison with the results of IBM ILOG CPLEX. The proposed algorithm was applied to an actual case of production planning at Woongjin Chemical, a leading manufacturer of filter products in South Korea. The seven-month execution of our algorithm led to a 24.5% decrease in the company's inventory level, thus demonstrating its practicality and effectiveness.

• Industrial Engineering and Management Systems
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• v.7 no.3
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• pp.204-213
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• 2008

Companies that produce capital goods need to schedule the production of products that have complex product structures with components that require many operations on different machines. A feasible schedule must satisfy operation and assembly precedence constraints. It is also important to avoid deadlock situations. In this paper a Genetic Algorithm (GA) has been developed that includes a new repair process that rectifies infeasible schedules that are produced during the evolution process. The algorithm was designed to minimise the combination of earliness and tardiness penalties and took into account finite capacity constraints. Three different sized problems were obtained from a collaborating capital goods company. A design of experimental approach was used to systematically identify that the best genetic operators and GA parameters for each size of problem.

• Korean Management Science Review
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• v.17 no.1
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• pp.41-54
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• 2000

in the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.

• 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.