• Title/Summary/Keyword: multi-heuristic algorithm

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Multi-objective Capacitor Allocations in Distribution Networks using Artificial Bee Colony Algorithm

  • El-Fergany, Attia;Abdelaziz, A.Y.
    • 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.

The Corrective Heuristic Algorithm Analysis of the N$\times$3 Flow-shop Problem and Comparative Study with Multi-model (N$\times$3 Flow-shop 문제에 대한 수정된 발견적기법 분석과 기존기법과의 비교연구)

  • 강석호;궁광호
    • 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.

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A GA-based Heuristic for the Interrelated Container Selection Loading Problems

  • Techanitisawad, Anulark;Tangwiwatwong, Paisitt
    • 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.

Scheduling for Mixed-Model Assembly Lines in JIT Production Systems (JIT 생산 시스템에서의 혼합모델 조립라인을 위한 일정계획)

  • Ro, In-Kyu;Kim, Joon-Seok
    • 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.

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Single-Row Routing Algorithm in Multilayer LSI (다층 LSI에 있어 Single-Row Routing Algorithm)

  • Jo, Joong-Hwi;Jeong, Jeong-Hwa;Im, In-Chil
    • 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.

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MULTI-ITEM SHELF-SPACE ALLOCATION OF BREAKABLE ITEMS VIA GENETIC ALGORITHM

  • MAITI MANAS KUMAR;MAITI MANORANJAN
    • 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.

Multi-Output Logic Minimization Algorithm Using the Concept of Ordering Set (순서(順序) 집합(集合) 개념(槪念)을 이용(利用)한 다출력(多出力) 논리함수(論理函數) 최소화(最小化) 알고리즘)

  • Baek, Young-Suck;Kim, Tae-Hun;Lee, Seong-Bong;Chong, Jong-Wha
    • 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.

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Multi-objective Unbalanced Distribution Network Reconfiguration through Hybrid Heuristic Algorithm

  • Mahendran, G.;Sathiskumar, M.;Thiruvenkadam, S.;Lakshminarasimman, L.
    • 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.

A Virtual Topology Management Policy in Multi-Stage Reconfigurable Optical Networks (다단계 재구성 가능한 광 네트워크상에서 가상 토폴로지 관리 정책)

  • Ji-Eun Keum;Lin Zhang;Chan-Hyun Youn
    • 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.

An Exact Solution Approach for Release Planning of Software Product Lines (소프트웨어 제품라인의 출시 계획을 위한 최적해법)

  • Yoo, Jae-Wook
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.35 no.2
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    • pp.57-63
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    • 2012
  • Software release planning model of software product lines was formulated as a precedence-constrained multiple 0-1 knapsack problem. The purpose of the model was to maximize the total profit of an entire set of selected features in a software product line over a multi-release planning horizon. The solution approach is a dynamic programming procedure. Feasible solutions at each stage in dynamic programming are determined by using backward dynamic programming approach while dynamic programming for multi-release planning is forward approach. The pre-processing procedure with a heuristic and reduction algorithm was applied to the single-release problems corresponding to each stage in multi-release dynamic programming in order to reduce the problem size. The heuristic algorithm is used to find a lower bound to the problem. The reduction method makes use of the lower bound to fix a number of variables at either 0 or 1. Then the reduced problem can be solved easily by the dynamic programming approaches. These procedures keep on going until release t = T. A numerical example was developed to show how well the solution procedures in this research works on it. Future work in this area could include the development of a heuristic to obtain lower bounds closer to the optimal solution to the model in this article, as well as computational test of the heuristic algorithm and the exact solution approach developed in this paper. Also, more constraints reflecting the characteristics of software product lines may be added to the model. For instance, other resources such as multiple teams, each developing one product or a platform in a software product line could be added to the model.