• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.127-137
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• 1999

This study is concerned with the loading problems in flexible manufacturing system(FMS). The loading problem in FMS is a complex one, when the number of machine and job is increased. It may be time-consuming and even impossible to achieve an optimal solution about this problem mathematically. Thus, a heuristic method is recommended in order to gain near-optimal solutions in a practically acceptable time. A new loading algorithm is developed with a multi-criterion objective of considering the workload unbalance, and maximizing the machine utilization, throughput for critical resources such as the number of tool slots and the number of working hours in a scheduling period and so on. The results of SAS analysis indicated that true average throughput of proposed heuristic loading statistically exceeds that of Shanker and Srinivasulus loading algorithm at the significance level of 0.1.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.441-451
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• 2014

This article addresses an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.

• Journal of the Korean Operations Research and Management Science Society
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• v.6 no.2
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• pp.13-19
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• 1981

This paper developed 3 flow-shop sequencing heuristic methods: modified RA method, modified RACS method and modified RAES method. These methods modified RA method, RACS method and RAES method developed by D. G. Dannenbring. These methods can easily determine desirable sequence of orders and can improve nx3 flow-shop's productivity and efficiency. The maximum flow-time criterion is selected as the evaluation criterion of flow-shop's efficiency, We evaluated these 6 heuristic methods’ performance. By the evaluation of the result, we can see that the modified methods produce a shorter maximum flow-time than the original methods.

• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.22-37
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• 2004

An integrated heuristic approach based on genetic algorithms (GAs) is proposed for solving the container selection and loading problems. The GA for container selection solves a two-dimensional knapsack problem, determining a set of containers to minimize the transportation or shipment cost. The GA for container loading solves for the weighted coefficients in the evaluation functions that are applied in selecting loading positions and boxes to be loaded, so that the volume utilization is maximized. Several loading constraints such as box orientation, stack priority, stack stability, and container stability are also incorporated into the algorithm. In general, our computational results based on randomly generated data and problems from the literature suggest that the proposed heuristic provides a good solution in a reasonable amount of computational time.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.83-94
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• 1991

This study is concerned with the scheduling problem for mixed-model assembly lines in Just-In-Time(JIT) production systems. The most important goal of the scheduling for the mixed-model assembly line in JIT production systems is to keep a constant rate of usage for every part used by the systems. In this study, we develop two heuristic algorithms able to keep a constant rate of usage for every part used by the systems in the single-level and the multi-level. In the single-level, the new algorithm generates sequence schedule by backward tracking and prevents the destruction of sequence schedule which is the weakest point of Miltenburg's algorithms. The new algorithm gives better results in total variations than the Miltenburg's algorithms. In the multi-level, the new algorithm extends the concept of the single-level algorithm and shows more efficient results in total variations than Miltenburg and Sinnamon's algorithms.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.4
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• pp.84-89
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• 1984

In the design of digital system, designers use multi-layer LSI to connect all signal sets between circuit modules. This paper suggests how to minimize upper street congestions and lower congestions in the single-row routing, a routing method of multi-layer LSI. This paper suggests the heuristic algorithm which minimize upper street congestions and lower street congestions by suggesting interval graph and relational operator and finding out of the order of signal sets The algorithm was implemented on a VAX-11/780 computer and illustrated by means of examples.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.327-343
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• 2006

A general methodology is suggested to solve shelf-space allocation problem of retailers. A multi-item inventory model of breakable items is developed, where items are either complementary or substitute. Demands of the items depend on the amount of stock on the showroom and unit price of the respective items. Also demand of one item decreases (increases) due to the presence of others in case of substitute (complementary) product. For such a model, a Contractive Mapping Genetic Algorithm (CMGA) has been developed and implemented to find the values of different decision variables. These are evaluated to have maximum possible profit out of the proposed system. The system has been illustrated numerically and results for some particular cases are derived. The results are compared with some other heuristic approaches- Simulated Annealing (SA), simple Genetic Algorithm (GA) and Greedy Search Approach (GSA) developed for the present model.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.525-528
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• 1988

In this paper, a new multi-output logic minimization algorithm is presented. A base minterm is selected in the given function and the prime implicant is obtained by expanding it in the order of the expansion set that is decided by heuristic method. Input-oriented expansion procedure is used to reduce fan-in and fan-out number. To show the effectiveness of this algorithm, comparative run time with other minimization algorithm is given.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.215-222
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• 2013

Electrical power distribution systems are critical links between the utility and customer. In general, power distribution systems have unbalanced feeders due to the unbalanced loading. The devices that dependent on balanced three phase supply are affected by the unbalanced feeders. This necessitates the balancing of feeders. The main objective of reconfiguration is to balance the loads among the phases subject to constraints such as load flow equations, capacity and voltage constraints and to reduce the real power loss, while subject to a radial network structure in which all loads must be energized. Therefore, the distribution system reconfiguration problem has been viewed as multi-objective problem. In this paper, the hybrid heuristic algorithm has been used for reconfiguration, which is the combination of fuzzy and greedy algorithms. The purpose of the introduction of greedy is to refrain the searching for the period of phase balancing. The incorporation of fuzzy helps to take up more objectives amid phase balancing in the searching. The effectiveness of the proposed method is demonstrated through modified IEEE 33 bus and modified IEEE 125 bus radial distribution system.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.1-8
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• 2003

In this paper. we develop an analytical model to evaluate the virtual topology reconfiguration phase of optical Internet networks. To counter the continual approximation problem brought by traditional heuristic approach, we take the traffic prediction into consideration and propose a new heuristic reconfiguration algorithm called Prediction based Multi-stage Reconfiguration approach. We then use this analytical model to study the different configuration operation policies in response to the changing traffic patterns in the higher layer and the congestion level on the virtual topology. This algorithm persists to decide the optimal instant of reconfiguration easily based on the network state. Simulation results show that our virtual topology management Policy significantly outperforms the conventional one, while the required physical resources are limited.