• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.79-86
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• 2012

This study focuses on the problem of scheduling wafer lots of several recipe(operation condition) types in the photolithography workstation in a semiconductor wafer fabrication facility, and sequence-dependent recipe set up times may be required at the photolithography machines. In addition, a lot is able to be operated at a machine when the reticle(mask) corresponding to the recipe type is set up in the photolithography machine. We suggest various heuristic algorithms, in which developed recipe selection rules and lot selection rules are used to generate reasonable schedules to minimizing the total weighted flowtime. Results of computational tests on randomly generated test problems show that the suggested algorithms outperform a scheduling method used in a real manufacturing system in terms of the total weighted flowtime of the wafer lots with ready times.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.204-212
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• 2008

We study the routing problem in all-wireless networks based on cooperative transmissions. We model the minimum-energy cooperative path (MECP) problem and prove that this problem is NP-complete. We hence design an approximation algorithm called cooperative shortest path (CSP) algorithm that uses Dijkstra's algorithm as the basic building block and utilizes cooperative transmissions in the relaxation procedure. Compared with traditional non-cooperative shortest path algorithms, the CSP algorithm can achieve a higher energy saving and better balanced energy consumption among network nodes, especially when the network is in large scale. The nice features lead to a unique, scalable routing scheme that changes the high network density from the curse of congestion to the blessing of cooperative transmissions.

• Journal of Industrial Technology
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• v.16
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• pp.217-230
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• 1996

This paper deals with storage and retrieval policies for S/R machine with capacity constraints in Man-On-Board AS/RS. It is assumed that storage sequence is based on SFC(spacefilling curve) routine and that storage layout is dedicated by storage policies. We present several heuristic algorithms for storage and retrieval policies which minimize total distance travelled by the S/R machine. These algorithms are based on COI, group COI, frequency of order, similarity between items and capacity of S/R machine. Experimental results of 24 combinastorial policies are provided to illustrate the performance of the heuristics under various rack utilization ratios. In storage policies, the results show that algorithms considering both similarity and frequency are better than those with COI as rack utilization is increasing. And algorithm using group COI is superior to others. In retrieval policies, the method with revision expression is shown to be better than others.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.9
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• pp.884-891
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• 2009

This study investigates some of swarm intelligence algorithms to tackle a traditional damage detection problem having stiffness degradation or damage in mechanical structures. Particle swarm(PSO) and ant colony optimization(ACO) methods have been exploited for localizing and estimating the location and extent damages in a structure. Both PSO and ACO are population-based, stochastic algorithms that have been developed from the underlying concept of swarm intelligence and search heuristic. A finite element (FE) model updating is implemented to minimize the difference in a set of natural frequencies between measured and baseline vibration data. Stiffness loss of certain elements is considered to simulate structural damages in the FE model. It is numerically shown that PSO and ACO algorithms successfully completed the optimization process of model updating in locating unknown damages in a truss structure.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.47-47
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• 1989

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.

• Architectural research
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• v.8 no.2
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• pp.43-48
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• 2006

The appropriate fleet estimation of the excavation equipment is a major factor in the determination of the cost and time requirements of a project. But the decision of what kind of equipment selected is often based on heuristic methods or trial and error in Korea. Thus, this study proposes a prototype model that uses genetic algorithms to select fleet estimation of loaders (backhoe) and trucks used in excavation work. To verify the applicability of this model, the case study was performed. And the result of the genetic model was compared with that of the trial & error method. The use of the genetic model suggested this study required 44days, 2 units of backhoes, 7 units of trucks, and a total cost of 171,839,756 won. With the estimated fleet number of equipment, the minimum cost of excavation work can be calculated, taking account of the time-cost trade-off. By utilizing this prototype model, the efficiency of excavation work can be improved.

• Management Science and Financial Engineering
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• v.16 no.1
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• pp.59-79
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• 2010

This paper considers bandwidth allocation and scheduling problems on Ethernet Passive Optical Networks (EPON). EPON is one of the good candidates for the optical access network. This paper formulates the bandwidth allocation problem as a nonlinear mathematical one and characterizes the optimal bandwidth allocation which maximizes weighted sum of throughput and fairness. Based upon the characterization, two heuristic algorithms are suggested with various numerical tests. The test results show that our algorithms can be used for efficient bandwidth allocation on the EPON. This paper also shows that the WSPT (Weighted Shortest Processing Time) rule is optimal for minimization the total delay time in transmitting the traffic of the given allocated bandwidth.

• Proceedings of the IEEK Conference
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• summer
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• pp.400-404
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• 2004

There are many methods to find solutions for Integer Programming problems (IPs) such as the Branch-Bound philosophy or the Cutting Plane algorithm. However, most of them have a problem that is the explosion of sets in the computing process. In addition, GA is known as a heuristic search algorithm for solutions of optimization problems. It is started from a random initial guess solution and attempting to find one that is the best under some criteria and conditions. The paper will study an artificial intelligent method to solve IPs by using Genetic Algorithms (GAs). The original solution of this was presented in the papers of Fabricio Olivetti de Francaand and Kimmo Nieminen [2003]. However, both have several limitations which causes could be operations in GAs. The paper proposes a method to upgrade these operations and computational results are also shown to support these upgrades.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.172-174
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• 1996

This paper presents a new approach on genetic algorithms to economic dispatch problem for valve point discontinuities. Although it has been already shown that genetic algorithm was more powerful to economic dispatch problem for valve point discontinuities than other optimization algorithms, proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through combination in penalty function with death penalty, generation-apart elitism and heuristic crossover. Numerical results on an actural utility system consisted of 13 thermal units show that the proposed approach is faster and robuster than the classical genetic algorithm.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.665-676
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• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.