• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.11
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• pp.79-83
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• 1985

This paper is to develop four heuristic algorithms for $n/m/D/F/F_{max}$. A study present numerical example for (H1) algorithm. Among the sequence generated, the best sequence is J2, J1, J6, J7, J4, J3, J5 and makespan is 528. The optimal makespan of this numerical example can be found as 528 as also, and the worst value of heuristic solution is only 7.2 % away from it.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.73-82
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• 1988

This research is concerned with production scheduling for FMS (Flexible Manufacturing System) which consists of machine centers served by cycle conveyor. The objective of the research is to develop and evaluate scheduling procedures to minimize the mean flow time. An optimal algorithm called SCTF (Shortest Circle Time First) is proposed when the conveyor runs at minimum possible speed (CS=1) and a heuristic algorithm called SCTJMF (Shortest Cycle Time and Job Matching Algorithm) is suggested when the conveyor runs at double speed (CS=2). The evaluation of the heuristic algorithm was implemented by comparison with the optimal algorithm for 112 experimentations for CS=1 and random schedule. The results showed that the proposed heuristic algorithm provides better solution that can be regarded noticeable when compared with SCTF algorithm and random scheduling.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.169-178
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• 1996

Geographically dispersed computing system is made of computers interconnected by a telecommunications network. To make the system operated efficiently, system designer must determine the allocation of data files to each node. In designing such distributed computing system, the most important issue is the determination of the numbers and the locations where database files are allocated. This is commonly referred to as the file allocation problem (FAP)[3]. The proposed model is a 0/l integer programming problem minimizing the sum of file storage costs and communication(query and update) costs. File allocation problem belongs to the class of NP-Complete problems. Because of the complexity, it is hard to solve. So, this paper presents an efficient heuristic algorithm to solve the file allocation problem using Tabu Search Technique. By comparing the optimal solutions with the heuristic solutions, it is believed that the proposed heuristic algorithm gives good solutions. Through the experimentation of various starting points and tabu restrictions, this paper presents fast and efficient method to solve the file allocation problem in the distributed computing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.626-648
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• 2011

Energy consumption of wireless access networks is in permanent increase, which necessitates development of more energy-efficient network management approaches. Such management schemes must result with adaptation of network energy consumption in accordance with daily variations in user activity. In this paper, we consider possible energy savings of wireless local area networks (WLANs) through development of a few integer linear programming (ILP) models. Effectiveness of ILP models providing energy-efficient management of network resources have been tested on several WLAN instances of different sizes. To cope with the problem of high computational time characteristic for some ILP models, we further develop several heuristic algorithms that are based on greedy methods and local search. Although heuristics obtains somewhat higher results of energy consumption in comparison with the ones of corresponding ILP models, heuristic algorithms ensures minimization of network energy consumption in an amount of time that is acceptable for practical implementations. This confirms that network management algorithms will play a significant role in practical realization of future energy-efficient network management systems.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.8-14
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• 2012

Two dimensional nesting is a common problem in industries such as the shipbuilding, automotive, clothing, shoe-making, and furniture industries, in which various parts are cut off from stock or packed in a flat space while minimizing waste or unoccupied space. Nesting is known as an NP-complete problem, which has a solution time proportional to the superpolynomial of the input size. It becomes practically impossible to find an optimal solution using algorithmic methods as the number of shapes to nest increases. Therefore, heuristic methods are commonly used to solve nesting problems. This paper presents an expert system that uses a heuristic search method based on an evaluation function for nesting problems, in which parts and stock are represented by pixels. The system is developed in CLIPS, an expert system shell, and is applied to four different kinds of example problems to verify its applicability in practical problems.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.91-98
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• 1990

This paper studies a heuristic method for the Maximum Origin-Destination Flow Path (MODFP) in an acyclic transportation network. We construct a mathematical formulation for finding the MODFP. Then by applying Benders' partitioning method, we generate two subproblems which should be solved in turn so that they may give an optimal solution. We solve one subproblem by an optimal seeking algorithm and the other by a hueristic method. so that, we finally obtain a good solution. The computational complexity of calculating the optimal solution of the first subproblem is 0(mn) and that of calculating the heuristic solution of the other subproblem is $0(n^2).$ From the computational experiments, we estimated the performance of the heuristic method as being 99.3% and the computing time relative to optimal algorithm as being 28.76%.

• IE interfaces
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• v.15 no.4
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• pp.338-348
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• 2002

In this paper, we present a restricted tabu search(RTS) algorithm that schedules jobs on identical parallel machines in order to minimize the maximum lateness of jobs. Jobs have release times and due dates. Also, sequence-dependent setup times exist between jobs. The RTS algorithm consists of two main parts. The first part is the MATCS(Modified Apparent Tardiness Cost with Setups) rule that provides an efficient initial schedule for the RTS. The second part is a search heuristic that employs a restricted neighborhood generation scheme with the elimination of non-efficient job moves in finding the best neighborhood schedule. The search heuristic reduces the tabu search effort greatly while obtaining the final schedules of good quality. The experimental results show that the proposed algorithm gives better solutions quickly than the existing heuristic algorithms such as the RHP(Rolling Horizon Procedure) heuristic, the basic tabu search, and simulated annealing.

• IE interfaces
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• v.12 no.4
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• pp.532-539
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• 1999

The first step to design a cellular manufacturing system is to make part-families and machine-cells. This process is called the machine-part grouping. This paper considers a machine-cell size when grouping machine-cells. By considering a machine-cell size, an unrealistically big size of machine-cell which may be caused by the chaining effect can be avoid. A heuristic algorithm which minimizes the number of inter-cell movement of parts considering a machine-cell size is presented. The effectiveness and performance of the proposed heuristic algorithm are compared with those of several heuristic algorithms previously reported. The comparison shows that the proposed heuristic algorithm is efficient and reliable in minimizing the number of inter-cell movement of parts and also prevents the chaining effect.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.3
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• pp.37-49
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• 1993

In this paper, the TSP(traveling salesman problem) which its costs(distance) between nodes are defined with Max($\bar{x}$, $\bar{y}$) has been dealt. In order to find a satisfactory solution for this kind of problem, we generate weighted matrix, and then develope a new heuristic problem solving method using the weighted matrix. Also we analyze the effectiveness of the newly developed heuristic method comparing it with other heuristic algorithm already exists for Euclidean TSP. Finally, we apply a new developed algorithm to real Max($\bar{x}$,$\bar{y}$) TSP such as PCB inserting.

• Management Science and Financial Engineering
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• v.12 no.1
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• pp.95-112
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• 2006

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used or end-of-life products while satisfying the demand of their parts and/or components over a planning horizon. The case of assembly product structure is considered while the resource capacity constraints are explicitly considered. A cost-based objective is considered that minimizes the sum of disassembly operation and inventory holding costs. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To test the performance of the heuristic, computational experiments are done on randomly generated problems, and the results show that the heuristic gives near optimal solutions within a very short amount of computation time.