• Title/Summary/Keyword: mixed-integer programming

검색결과 389건 처리시간 0.034초

An Algorithm for Portfolio Selection Model

  • Kim, Yong-Chan;Shin, Ki-Young;Kim, Jong-Soo
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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    • pp.65-68
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    • 2000
  • The problem of selecting a portfolio is to find Un investment plan that achieves a desired return while minimizing the risk involved. One stream of algorithms are based upon mixed integer linear programming models and guarantee an integer optimal solution. But these algorithms require too much time to apply to real problems. Another stream of algorithms are fur a near optimal solution and are fast enough. But, these also have a weakness in that the solution generated can't be guaranteed to be integer values. Since it is not a trivial job to tansform the scullion into integer valued one simutaneously maintaining the quality of the solution, they are not easy to apply to real world portfolio selection. To tackle the problem more efficiently, we propose an algorithm which generates a very good integer solution in reasonable amount of time. The algorithm is tested using Korean stock market data to verify its accuracy and efficiency.

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다목적 유전 알고리듬을 이용한 혼합모델 조립라인의 최적 생산순서계획 (Mixed-Model Sequencing Using Genetic Algorithms with Multiple Evaluation Criteria)

  • 김연민;김영진
    • 산업공학
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    • 제13권2호
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    • pp.204-210
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    • 2000
  • This paper deals with the problem of mixed-model sequencing on an assembly line. In this sequencing problem we want to minimize the risk of the conveyor stoppage and the total utility work. This paper applies genetic algorithm to solve the mixed-model sequencing problem which is formulated as an integer programming. The solution we get from this algorithm is compared with the solution of Tsai(1995)'s.

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수리계획모형을 활용한 대도시 폐기물 관리 시스템의 광역화 운영 계획에 관한 연구 (A Study on the Regionalization of the Municipal Solid Waste Management System Using a Mathematical Programming Model)

  • 김재희;김승권;이용대
    • 경영과학
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    • 제20권1호
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    • pp.65-76
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    • 2003
  • The increased environmental concerns and the emphasis on recycling are gradually shifting the orientation of municipal solid waste (MSW) management. This paper is designed to evaluate regionalization programs for MSW management system. We developed a mixed intiger network programming (MIP) model to identify environment-friendly, cost-effective expansion plans for regionalization scenarios considered. The MIP model is a dynamic capacity expansion model based on the network flow model that depicts the MSW management cycle. In particular, our model is designed to determine the optimal form of regionalization using binary variables. We apply this model to assess the regionalization program of Seoul Metropolitan City, which includes three scenarios such as 1) districting, 2) regionalization with neighboring self-governing districts, and 3) g1obalization with all districts. We demonstrate how our model can be used to plan the MSW system. The results indicate that optimal regionalization with nearby self-governing districts can eliminate unnecessary landfills and expansions if jurisdictional obstacles are removed.

MINIMIZATION OF PARENT ROLL TRIM LOSS FOR THE PAPER INDUSTRY

  • Bae, Hee-Man
    • 한국경영과학회지
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    • 제3권2호
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    • pp.95-108
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    • 1978
  • This paper discusses an application of mathematical programming techniques in the paper industry in determining optimal parent roll widths. Parent rolls are made from the reels produced at wide paper machines by slitting them to more manageable widths. The problem is finding a set of the slitting patterns that will minimize the trim loss involved in the sheeting operation. Two programming models, one linear and one mixed integer linear, are presented in this paper. Also presented are the computational experience, the model sensitivity, and the comparison of the optimal solutions with the simulated operational data.

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An Optimization Procedure for a Multi-Item Multi-Source Materials Acquisition Problen

  • Kim, Jae-Yearn
    • 대한산업공학회지
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    • 제10권1호
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    • pp.3-10
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    • 1984
  • A materials acquisition planning (MAP) problem that involves the determination of how much to order of a number of different items from a number of different suppliers is considered. This particular problem is modelled as a nonlinear mixed integer programming problem. A solution procedure based upon the partition of variables is developed to handle the MAP problem. This solution procedure utilizes a modified Hooke-Jeeves Pattern Search procedure along with a linear programming simplex algorithm. An example problem is presented and the results of applying the suggested solution procedure to this problem are reported.

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복합화물 터미널 립지선정을 위한 수학적 계획모형의 정립과 적용 (A Mathematical Programming Model for the Freight Terminal Location Problem)

  • 이금숙;강승필
    • 대한교통학회지
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    • 제8권1호
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    • pp.41-54
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    • 1990
  • The rapid increase in the freight movement in Korea demands the improvement of the freight transportation system both in quantity and in quality. In recent studies integrated freight terminals have been suggested as the most relevant physical facility that solves this problem. This paper is aiming at the efficiency of the freight transportation system in Korea via integrated freight terminals. We develop a mixed integer programming model to determine simultaneously the most efficient freight flow patterns as well as the optimal locations and sizes of the integrated freight terminal facilities. The results of the model implication is also presented.

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혼합정수 선형계획법과 유전 알고리듬을 이용한 다수 무인항공기 임무할당 (Task Assignment of Multiple UAVs using MILP and GA)

  • 최현진;서중보;김유단
    • 한국항공우주학회지
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    • 제38권5호
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    • pp.427-436
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    • 2010
  • 본 논문은 다수의 목표물과 다수의 임무가 존재하는 상황에서의 다수 무인항공기의 임무할당 문제를 다룬다. 다수 무인항공기의 임무할당 문제는 순회 세일즈맨 문제, 차량 라우팅 문제와 같은 조합최적화 문제의 일종으로 NP-hard의 계산 복잡도를 가지고 있다. 이런 성격의 문제는 문제의 크기가 커질수록 계산시간이 급격히 증가하는 특징을 지니기 때문에 문제를 효율적으로 풀기 위해서 근사화 방법 또는 발견적인 방법을 사용한다. 본 연구에서는 임무할당 문제를 혼합정수 선형계획 문제로 정식화하고, 혼합정수 선형계획법과 유전 알고리듬으로 해를 구하였다. 다수의 목표물, 다수의 임무, 장애물이 존재하는 환경에 대한 수치 시뮬레이션을 수행하여 각 방법의 최적성과 효율성에 대해 검토하였다.

혼합정수계획법 및 유전자 알고리즘을 이용한 다품목 재고 시스템의 주문 주기 상쇄에 관한 연구 (Offsetting Inventory Cycle of Items Sharing Storage using Mixed Integer Programming & Genetic Algorithm)

  • 문일경;차병철;김선권
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2003년도 추계학술대회 및 정기총회
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    • pp.81-84
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    • 2003
  • The ability to determine the optimal frequencies and offsets for independent and unrestricted ordering cycles for multiple items can be very valuable for managing storage capacity constrained facilities in a supply chain. The complexity of this problem has resulted in researchers focusing on more tractable surrogate problems that are special cases of the base problem. Murthy et al. (European Journal of Operation Research 2003) developed insights leading to solution of the original problem and present a heuristic for offsetting independent and unrestricted ordering cycles for items to minimize their joint storage requirements. However, their study cannot find optimal solution due to the Greedy Heuristic solution procedure. In this paper, we present a complete procedure to find the optimal solution for the model with a integer programming optimization approach and genetic algorithm. Numerical examples are included to compare each model with that of Murthy et at. Research of this type may prove useful in solving the more general problem of selecting order policies to minimize combined holding, ordering, and storage costs.

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Integrated Inventory-Distribution Planning in a (1 : N) Supply Chain System with Heterogeneous Vehicles Incorporated

  • Kim, Eun-Seok;Lee, Ik-Sun
    • Management Science and Financial Engineering
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    • 제17권2호
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    • pp.1-21
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    • 2011
  • This paper considers an integrated inventory-distribution system with a fleet of heterogeneous vehicles employed where a single warehouse distributes a single type of products to many spatially distributed retailers to satisfy their dynamic demands. The problem is to determine order planning at the warehouse, and also vehicle schedules and delivery quantities for the retailers with the objective of minimizing the sum of ordering cost at the warehouse, inventory holding cost at both the warehouse and retailers, and transportation cost. For the problem, we give a Mixed Integer Programming formulation and develop a Lagrangean heuristic procedure for computing lower and upper bounds on the optimal solution value. The Lagrangean dual problem of finding the best Lagrangrean lower bound is solved by subgradient optimization. Computational experiments on randomly generated test problems showed that the suggested algorithm gives relatively good solutions in a reasonable amount of computation time.