• 대한산업공학회지
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• 제35권4호
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• pp.257-265
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• 2009

This paper considers the hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. In hybrid flow shops, each job is processed through multiple production stages in series, each of which has multiple identical parallel machines. The problem is to determine the allocation of jobs to the parallel machines at each stage as well as the sequence of the jobs assigned to each machine. Due to the complexity of the problem, we suggest search heuristics, tabu search and simulated annealing algorithms with a new method to generate neighborhood solutions. In particular, to evaluate and select neighborhood solutions, three surrogate objectives are additionally suggested because not much difference in the number of tardy jobs can be found among the neighborhoods. To test the performances of the surrogate objective based search heuristics, computational experiments were performed on a number of test instances and the results show that the surrogate objective based search heuristics were better than the original ones. Also, they gave the optimal solutions for most small-size test instances.

• 대한산업공학회지
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• 제33권2호
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• pp.213-220
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• 2007

This paper considers a two-stage hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. Each job is processed through the two production stages in stages, each of which has multiple identical parallel machines. The problem is to determine the allocation and sequence of jobs at each stage. A branch and bound algorithm that gives the optimal solutions is suggested that incorporates the methods to obtain the lower and upper bounds. Dominance properties are also suggested to reduce the search space. To show the performance of the algorithm, computational experiments are done on randomly generated problems, and the results are reported.

• 경영과학
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• 제12권3호
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• pp.177-185
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• 1995

This paper presents a Tabu Search method to minimize a number of tardy jobs in the nonidentical parallel machine scheduling. The Tabu Search method employs a restricted neighborhood for the reduction of computation time. In this paper, we use two different types of method for a single machine scheduling. One is Moore's algorithm and the other is insertion method. We discuss computational experiments on more than 1000 test problems.

• 대한산업공학회지
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• 제24권1호
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• pp.37-50
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• 1998

This paper considers the nonidentical parallel machine scheduling problem in which n jobs having different due dates are to be scheduled on m nonidentical parallel machines. For the make-to-order manufacturing environment, the objective is to minimize the number of tardy jobs. A 0-1 nonlinear programming model is formulated and a heuristic algorithm that allocates and sequences jobs to machines is developed. The proposed algorithm makes use of the concept of assignment problem based on the suitability measure as the cost coefficient. Computational experiments show that the proposed algorithm is superior to the existing one in some performance measures such as number of tardy jobs. In addition, this algorithm is appropriate for solving real industrial problems efficiently.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1133-1138
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• 2006

This paper considers a hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. The hybrid flow shop consists of two stages in series, each of which has multiple identical parallel machines, and the problem is to determine the allocation and sequence of jobs at each stage. A branch and bound algorithm that gives the optimal solutions is suggested that incorporates the methods to obtain the lower and upper bounds. Dominance properties are also derived to reduce the search space. To show the performance of the algorithm, computational experiments are done on randomly generated problems, and the results are reported.

• 산업경영시스템학회지
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• 제22권53호
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• pp.23-35
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• 1999

Since on-time delivery is becoming increasingly important in today's competitive markets, the development of effective scheduling methodologies to meet customer needs through on time delivery is of vital importance for the well-being of companies. The objective of this study is to develope a general heuristic algorithm for scheduling both the static and dynamic problems under certain on-time delivery criteria. For the problems with due-date related, we present insights for minimizing the number of tardy jobs and propose a heuristic scheduling algorithm. Experimental results show that the proposed algorithm performs significantly better than other dispatching rules within reasonable computation time, specially in the environment of strong competition for resources.

• 한국컴퓨터정보학회논문지
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• 제21권9호
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.

• 한국컴퓨터정보학회논문지
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• 제23권3호
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• pp.85-92
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• 2018

We consider a project scheduling problem in which the jobs can be compressed by using additional resource to meet the corresponding due dates, referred to as a time-cost tradeoff problem. The project consists of two independent subprojects of which precedence graph is a chain. The due dates of jobs constituting the project can be interpreted as the multiple assessments in the life of project. The penalty cost occurs from the tardiness of the job, while it may be avoided through the compression of some jobs which requires an additional cost. The objective is to find the amount of compression that minimizes the total tardy penalty and compression costs. Firstly, we show that the problem can be decomposed into several subproblems whose number is bounded by the polynomial function in n, where n is the total number of jobs. Then, we prove that the problem can be solved in polynomial time by developing the efficient approach to obtain an optimal schedule for each subproblem.

• 산업경영시스템학회지
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• 제20권43호
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• pp.81-89
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• 1997

This study is concerned with the scheduling problems in flexible manufacturing systems(FMSs). The scheduling problem in FMSs is a complex one when the number of machines and jobs are increased. Thus, a heuristic method is recommended in order to gain near-optimal solutions in a practically acceptable time. The purpose of this study is to develope a machine and AGV dispatching algorithm. The proposed dispatching algorithm is a on-line scheduling algorithm considering the due date of parts and the status of the system in the scheduling process. In the new machine and AGV dispatching algorithm, a job priority is determined by LPT/LQS rules considering job tardiness. The proposed heuristic dispatching algorithm is evaluated by comparison with the existing dispatching rules such as LPT/LQS, SPT/LQS, EDD/LQS and MOD/LQS. The new dispatching algorithm is predominant to existing dispatching rules in 100 cases out of 100 for the mean tardiness and 89 cases out of 100 for the number of tardy jobs.

• Journal of applied mathematics & informatics
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• 제17권1_2_3호
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• pp.419-432
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• 2005

In this paper we study the no-wait or no-idle permutation flowshop scheduling problem with an increasing and decreasing series of dominating machines. The objective is to minimize one of the five regular performance criteria, namely, total weighted completion time, maximum lateness, maximum tardiness, number of tardy jobs and makespan. We establish that these five cases are solvable by presenting a polynomial-time solution algorithm for each case.