• Title/Summary/Keyword: Heuristic cost function

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On the Multi-Stage Group Scheduling with Dependent Setup Time (종속적 준비시간을 갖는 다단계 그룹가공 생산시스템에서의 그룹스케듈링에 관한 연구)

  • 황문영
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.17 no.31
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    • pp.115-123
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    • 1994
  • Group scheduling, which is a kind of operations scheduling based on the GT concept is analyzed in a multi-stage manufacturing system. The purpose of this research is to develop and evaluate a heuristic algorithm for determining gro up sequence and job sequence within each group to minimize a complex cost function, i.e. the sum of the total pe-nalty cost for tardiness and the total holding cost for flow time, in a multi-stage manufacturing system with group setup time dependent upon group sequence. A heuristic algorithm for group sc heduling is developed, and a numerical example is illustrated. For the evaluation of the pro-posed heuristic algorithm, the heuristic solution of each of 63 problems is compared with that of random scheduling. The result shows that the proposed heuristic algorithm provides better solution in light of the proposed cost function.

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The Use of Particle Swarm Optimization for Order Allocation Under Multiple Capacitated Sourcing and Quantity Discounts

  • Ting, Ching-Jung;Tsai, Chi-Yang;Yeh, Li-Wen
    • Industrial Engineering and Management Systems
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    • v.6 no.2
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    • pp.136-145
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    • 2007
  • The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

Facial Features Detection Using Heuristic Cost Function (얼굴의 특성을 반영하는 휴리스틱 평가함수를 이용한 얼굴 특징 검출)

  • Jang, Gyeong-Sik
    • The KIPS Transactions:PartB
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    • v.8B no.2
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    • pp.183-188
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    • 2001
  • 이 논문은 눈의 형태에 대한 정보를 이용하여 눈동자를 효과적으로 찾는 방법과 얼굴 특성을 반영하는 평가함수를 이용하여 눈동자, 입의 위치와 같은 얼굴 특징들을 인식하는 방법을 제안하였다. 색 정보를 이용하여 입술과 얼굴 영역을 추출하고 눈동자와 흰자위간의 명도 차를 이용하는 함수를 사용하여 눈동자를 인식하였다. 마지막으로 얼굴 특성을 반영하느 평가함수를 정의하고 이를 이용하여 최종적인 얼굴과 눈, 입을 인식하였다. 제안한 방법을 사용하여 여러 영상들에 대해 실험하여 좋은 결과를 얻었다.

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A Study for Solving Multi-Depot Dial-a-Ride Problem Considering Soft Time Window (다수차고지와 예약시간 위반을 고려한 교통약자 차량 서비스에 대한 연구)

  • Kim, Taehyeong;Park, Bum-Jin;Kang, Weon-Eui
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.5
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    • pp.70-77
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    • 2012
  • Dial-a-ride is the most widely available transit service for disabled persons or seniors in the United States and Europe. This paper studies a static dial-a-ride problem considering multiple depots, heterogeneous vehicles, and soft time windows. In this paper, we apply a heuristic based on clustering first-routing second(HCR) to a real-world large dial-a-ride problem from Maryland Transit Administration(MTA). MTA's real operation is compared with the results of developed heuristic for 24 cases. The objective function of the proposed model is to minimize the total cost composed of the service provider's cost and the customers' inconvenience cost. For the comparison, the objective function values of HCR do not include waiting cost, delay cost, and excess ride cost. The objective function values from HCR are better than those from MTA's operation for all cases. This result shows that our heuristic method can make the real operation better and more efficient.

Optimal Feeder Routing for Distribution System Planning Using a Heuristic Strategy (휴리스틱 탐색전략을 이용한 배전계통 계획의 급전선 최적 경로 선정)

  • Choi, Nam-Jin;Kim, Byung-Seop;Shin, Joong-Rin
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.49 no.11
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    • pp.566-574
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    • 2000
  • This paper propose a heuristic algorithm based on the Branch-Exchange (BE) method to solve Optimal feeder Routing(OFR) problem for the distribution system planning. The cost function of the OFR problem is consisted of the investment cost representing the feeder installation and the system operation cost representing the system power loss. We propose a properly designed heuristic strategy, which can handle the horizon-year expansion planning problem of power distribution network. We also used the loop selection method which can define the maximum loss reduction in the network to reduce calculation time, and proposed a new index of power loss which is designed to estimate the power loss reduction in the BE. The proposed index, can be considered with both sides, the low voltage side and voltage side branch connected with tie one. The performances of the proposed algorithms and loss index were shown with 32, 69 example bus system.

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An Ant Colony Optimization Heuristic to solve the VRP with Time Window (차량 경로 스케줄링 문제 해결을 위한 개미 군집 최적화 휴리스틱)

  • Hong, Myung-Duk;Yu, Young-Hoon;Jo, Geun-Sik
    • The KIPS Transactions:PartB
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    • v.17B no.5
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    • pp.389-398
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    • 2010
  • The Vehicle Routing and Scheduling Problem with Time Windows(VRSPTW) is to establish a delivery route of minimum cost satisfying the time constraints and capacity demands of many customers. The VRSPTW takes a long time to generate a solution because this is a NP-hard problem. To generate the nearest optimal solution within a reasonable time, we propose the heuristic by using an ACO(Ant Colony Optimization) with multi-cost functions. The multi-cost functions can generate a feasible initial-route by applying various weight values, such as distance, demand, angle and time window, to the cost factors when each ant evaluates the cost to move to the next customer node. Our experimental results show that our heuristic can generate the nearest optimal solution more efficiently than Solomon I1 heuristic or Hybrid heuristic applied by the opportunity time.

Development of Query Transformation Method by Cost Optimization

  • Altayeva, Aigerim Bakatkaliyevna;Yoon, Youngmi;Cho, Young Im
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.1
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    • pp.36-43
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    • 2016
  • The transformation time among queries in the database management system (DBMS) is responsible for the execution time of users' queries, because a conventional DBMS does not consider the transformation cost when queries are transformed for execution. To reduce the transformation time (cost reduction) during execution, we propose an optimal query transformation method by exploring queries from a cost-based point of view. This cost-based point of view means considering the cost whenever queries are transformed for execution. Toward that end, we explore and compare set off heuristic, linear, and exhaustive cost-based transformations. Further, we describe practical methods of cost-based transformation integration and some query transformation problems. Our results show that, some cost-based transformations significantly improve query execution time. For instance, linear and heuristic transformed queries work 43% and 74% better than exhaustive queries.

A study on a schedule-cost analysis model for defense R&D project planning (국방 R&D프로젝트의 일정-비용분석모델의 연구)

  • 황홍석;류정철;정덕길
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.04a
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    • pp.213-216
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    • 1996
  • R'||'&'||'D project management is a process of decisions concerned with the achievement of goals of objectives. Especially, defense R'||'&'||'D project planning is the key in the successfull management of defense development. The defense project managers are constantly having to perform "what if\ulcorner" exercise, such as what if the project is extended out for an additional cost\ulcorner In this reserch, we developed a schedule-cost analysis model based upon Critical Path Method(CPM) and Venture Evaluation and Review Technique(VERT) for schedule-cost trade off analysis defense R'||'&'||'D projects. In the first step, a deterministic model is developed as a heuristic which deterministic model is developed as a heuristic which determines the schedule extension and reduction cost as a function desired schedule. In the second step, a stochastic network simulation model is developed to analyse the project risk (sucess and failure). The expected time and cost can be determined for desired schedule under the assumptions of stochastic arc data (time and cost) with a various precedence relationships. This model provides the defense R'||'&'||'D managers with an estimated and expected cost for curtailing or extending a project a given amount of time. The effectiveness and efficiency of the proposed methods, a heuristic and stochastic networks simulations, have been demonstrated through examples.

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Implementation and Evaluation of Path-Finding Algorithm using Abstract Graphs (추상 그래프를 활용한 경로 탐색 알고리즘의 구현 및 성능 평가)

  • Kim, Ji-Soo;Lee, Ji-wan;Cho, Dae-Soo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.245-248
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    • 2009
  • Recently, Many studies have been progressing to path-finding with dynamic information on the Terminal Based Navigation System(TBNS). However, the most of existing algorithms are based on $A{\ast}$ algorithm. Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, two abstract graph(AG) that are different method of construction, Homogeneous Node merging($AG^H$) and Connected Node Merging($AG^C$), are implemented. The abstract graph is a simple graph of real road network. The method of using the abstract graph is proposed for reducing dependency of heuristic and exploring cost. In result of evaluation of performance, $AG^C$ has better performance than $AG^H$ at construction cost but $AG^C$ has worse performance than $AG^H$ exploring cost.

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A Novel Heuristic Mechanism for Highly Utilizable Survivability on WDM Mesh Networks

  • Jeong Hong-Kyu;Kim Byung-Jae;Kang Min-Ho;Lee Yong-Gi
    • 한국정보통신설비학회:학술대회논문집
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    • 2003.08a
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    • pp.159-162
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    • 2003
  • This paper presents a novel heuristic mechanism, Dynamic-network Adapted Cost selection (DAC-selection), which has higher backup path sharing rate, lower number of blocked channel requests and number of used wavelengths fer reservation of working path and backup path by using unique cost function than that of widely used random selection (R-selection) mechanism and Combined Min-cost selection (CMC-selection) mechanism proposed by Lo, while maintaining 100% restoration capability.

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