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Parallel Machines Scheduling with GoS Eligibility Constraints
Kyungkuk Lim(임경국) 대한산업공학회 2010 대한산업공학회지 Vol.36 No.4
In this paper, we survey the parallel machines scheduling problem with GoS eligibility constraints so as to minimize the makespan. Our survey covers off-line, online and semi-online scheduling problems. In the case of online scheduling, we only focus on online scheduling one by one. Hence we give an introduction to the problem and present important results of the problem.
박종호(Jongho Park),임경국(Kyungkuk Lim),최봉하(Bongha Choi) 대한산업공학회 2008 대한산업공학회지 Vol.34 No.4
We consider the batch processing of orders where either whole or part of a single order or a specific pair of different orders may be grouped in a batch within a fixed capacity. Our objective is to maximize the total number of batches filled up to the batch size. In this paper, we study the Level-2 problem where at most 2 kinds of orders can be grouped in a batch. This problem is known to be NP-hard and Max SNP-hard. So we develop heuristic algorithm and evaluate the performance of the algorithm.
박종호(Jongho Park),임경국(Kyungkuk Lim),이정원(Jeongwon Lee) 대한산업공학회 2008 대한산업공학회지 Vol.34 No.4
Loading steel coil products on a specialized packing case called pallet can be represented as a bin-packing problem with the special constraint where objects should be loaded on designated positions of bins. In this paper, under assuming that there exist only two types of objects, we focus on finding the optimum number of positions in a bin which minimizes the number of bins needed for packing a collection of objects. Firstly, we propose a method to decide the number of positions and prove that the method is optimum. Finally, for the packing problem using bins designed by the method, we show that the well-known algorithm, First-Fit Decreasing(FFD), is the optimum algorithm.
작업이 일반적인 자격을 갖는 상황에서 3대의 기계와 4대의 기계의 온라인 스케줄링 문제에 대한 소고
박종호(Jongho Park),장수영(Soo Y. Chang),임경국(Kyungkuk Lim) 대한산업공학회 2009 대한산업공학회지 Vol.35 No.3
We consider the online scheduling problems of three and four machines under eligibility constraint. Respectively for the cases of three and four machines, we prove that AW algorithm has competitive ratios of 5/2 and 3 which are shown to be optimal. Also, we show that the same results hold for the semi-online cases with prior knowledge of the total and the largest processing time.