• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.310-313
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• 1996

Mathematical programming method for finding optimal solution of job shop scheduling is inadequate to real situation because fo too much computation time. In contrast, dispatching rule is helpful for reducing compuation time but is not guaranted to find optimal solution. The purpose of this paper is to develop a new dispatching rule and procedure to minimize mean flow time whose result is near the optimal solution for job shop scheduling. First step is to select machine which have shortest finishing operation time among the schedulable operations. Second step is to select operation with regard to estimated remaining operation time. The suggested rule is compared with nondelay and MWKR rule for three examples, and is confirmed to be most effective to minimize mean flow time.

• 한국경영과학회지
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• 제26권2호
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• pp.69-83
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• 2001

The problem of minimizing total tardiness on a batch processing machine with incompatible job families when there are sequence independent setup times between families is studied where all jobs of the same family have identical processing times and jobs of different families cannot be processed together. A batch processing machine can process a number of jobs, within a maximal batch size, simultaneously as a batch. The processing time required of each batch is equal to the one of jobs. A dynamic programming algorithm which gives the optimal solution, and several heuristics are presented. Performance of simple dispatching rules based on due dates are compared, and the best of them is used as an initial solution for the decomposition algorithm, which is shown to give good schedules in relatively short computational time.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.1071-1076
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• 2003

Evolutionary algorithm is recognized as a promising approach to solving multi-objective combinatorial optimization problems. When no preference information of decision makers is given, multi-objective optimization problems have been commonly used to search for diverse and good Pareto optimal solution. In this paper we propose a new multi-objective evolutionary algorithm based on competitive coevolutionary algorithm, and demonstrate the applicability of the algorithm. The proposed algorithm is designed to promote both population diversity and rapidity of convergence. To achieve this, the strategies of fitness evaluation and the operation of the Pareto set are developed. The algorithm is applied to job shop scheduling problems (JSPs). The JSPs have two objectives: minimizing makespan and minimizing earliness or tardiness. The proposed algorithm is compared with existing evolutionary algorithms in terms of solution quality and diversity. The experimental results reveal the effectiveness of our approach.

• 산업경영시스템학회지
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• 제21권47호
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• pp.125-138
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• 1998

In this paper, we investigate the effect of re-entrance to the same work station in a job shop with multiple identical machines. System A is defined as the system in which re-entrance is not permitted, and system B is defined as the system in which re-entrance is permitted. By the analytical result of the queueing network, we find that the two systems have the same queue length distributions and utilizations under FIFO dispatching rule when all parameters are same. Simulation models are developed for various comparisons between the two systems, and simulation experiments are conducted for the combinations of five dispatching rules, two average workloads and two due date allowances. Five performance measures are selected for the comparison. The simulation results show that permitting re-entrance affects for some combinations of system environments.

• 경영과학
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• 제10권1호
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• pp.171-192
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• 1993

In this paper, a rule for dispatching operations, named the Most Dissimilar Resources (MDR) dispatching rule is presented. The MDR dispatching rule has been designed to maximize utilization of resources in a resource-constrained job shop with general precedence constraints. In shown that solving the above scheduling problem with the MDR dispatching rule is equivalent to multiple solving of the maximum clique problem. A graph theoretic approach is used to model the latter problem. The pairwise counting heuristic of computational time complexity O(n$^{2}$) is developed to solve the maximum clique problem. An attempt is made to combine the MDR dispatching rule with the existing look-ahead dispatching rules. Computational experience indicates that the combined MDR dispatching rules provide solutions of better quality and consistency than the dispatching rules tested in a resource-constrained job shop.

• 대한안전경영과학회지
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• 제13권4호
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• pp.125-137
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• 2011

Customers are generally requiring a variety of products, earlier due date, and lower price. A manufacturing process needs the efficient scheduling to meet those customer's requirements. This study proposes the novel algorithm named MJA(Minimum Job completion time and AGV time) that increases the performance of machines and AGV(Automated Guided Vehicles) in many kinds of job types. MJA optimizes the bottleneck of machines and efficiency of AGV with considering two types of dispatching at the same time. Suggested algorithm was compared with existing heuristic methods by several simulations, it performed better for reducing the time of tardiness.

• 산업경영시스템학회지
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• 제15권25호
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• pp.23-31
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• 1992

This paper is concerned with an n jobs one machine Job shop scheduling problems in which all jobs have a common due date and unequal penalties occur when a job is completed before or after due date. The objective is to determine an optimal sequence and the corresponding common due date that yield the global minimum value of a penalty function Then a sequence that minimize the penalty function globally is a V-shaped sequence Using the idea of linear equations and a LGP(Linear Goal Programming), this paper shows that LGP and MAD(Mean Absolute Deviation) are equivalent problems. Therefore an efficient algorithm that is developed for MAD problem holds for LGP problem and vice-versa. A numerical example to account for the algorithm is provided.

• 대한기계학회논문집A
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• 제24권8호
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• pp.2131-2142
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• 2000

As recent production facilities are usually operated with unmanned material-handling system, the development of an efficient schedule with deadlock avoidance becomes a critical problem. Related researches on deadlock avoidance usually focus on real-time control of manufacturing system using deadlock avoidance policy. But little off-line optimization of deadlock-free schedule has been reported. This paper presents an optimization method for deadlock-free scheduling for Job-Shop system with no buffer. The deadlock-free schedule is acquired by the procedure that generates candidate lists of waiting operations, and applies a deadlock avoidance policy. To verify the proposed approach, simulation resultsare presented for minimizing makespan in three problem types. According to the simulation results the effect of each deadlock avoidance policy is dependent on the type of problem. When the proposed LOEM (Last Operation Exclusion Method) is employed, computing time for optimization as well as makespan is reduced.

• 대한조선학회논문집
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• 제60권3호
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• pp.202-211
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• 2023

The profile shops in shipyards produce section steels required for block production of ships. Due to the limitations of shipyard's production capacity, a considerable amount of work is already outsourced. In addition, the need to improve the productivity of the profile shops is growing because the production volume is expected to increase due to the recent boom in the shipbuilding industry. In this study, a scheduling optimization was conducted for a parallel welding line of the profile process, with the aim of minimizing tardiness and the number of set-up changes as objective functions to achieve productivity improvements. In particular, this study applied a dynamic scheduling method to determine the job sequence considering variability of processing time. A Markov decision process model was proposed for the job sequence problem, considering the trade-off relationship between two objective functions. Deep reinforcement learning was also used to learn the optimal scheduling policy. The developed algorithm was evaluated by comparing its performance with priority rules (SSPT, ATCS, MDD, COVERT rule) in test scenarios constructed by the sampling data. As a result, the proposed scheduling algorithms outperformed than the priority rules in terms of set-up ratio, tardiness, and makespan.

• 산업경영시스템학회지
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• 제16권27호
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• pp.91-104
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• 1993

This paper is concerned with flow shop scheduling problems having the common due date. V-shape property is used for algorithms with early and tardy penalty cost. The objective of this paper is developing efficient heuristic scheduling algorithms for minimizing total penalty cost function and determining the optimal common due date. The between job delay and the work in process are considered for developing algorithms as penalty cost. Algorithms is simulated to analyze interrelated factors. A numerical example is given for illustrating the proposed algorithms.