• Title/Summary/Keyword: Mixed Integer Programming Model

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A Study on the Validity of the Infrastructure Construction Cost for the Commercialization of Online Electric Vehicles (온라인 전기자동차의 상용화를 위한 인프라 구축비용 타당성에 대한 연구)

  • Song, Yong Uk;Park, Sangun;Kim, Wooju;Hong, June S.;Jeon, DongKyu;Lee, Sangheon;Park, Jonghan
    • The Journal of Society for e-Business Studies
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    • v.18 no.1
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    • pp.71-95
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    • 2013
  • This study aims to validate the cost of building the infrastructure to commercialize online electric vehicles. For that purpose, we probe the cost to construct the necessary infrastructure for online electric vehicles regarding Seoul area public bus transit. OLEV and PEV are considered as alternative electric vehicle schemes, and each of them has their own cons and pros in terms of rechargeable battery cost and charger cost. An optimization model which minimizes the cost to install online electric bus feeding devices is proposed in order to compare the total costs of the two alternative schemes. We developed a Mixed Integer Programming model to locate the feeding devices of several different lengths at each bus stops. Furthermore, we implemented a computer simulator to obtain the parameters which will be used in the MIP model and a Web-based system which determines the optimal location of infrastructure for the whole city area from a result of the MIP model. The cost comparison result shows that the total cost of OLEV is cheaper than that of PEV considering the real data of Seoul area public transit, and, as a result, confirms the feasibility of the commercialization of OLEV.

Dynamic Programming Approach for Prize Colleting Travelling Salesman Problem with Time Windows (시간제약이 있는 상금 획득 외판원 문제에 대한 동적 계획 접근 방법)

  • Tae, Hyun-Chul;Kim, Byung-In
    • IE interfaces
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    • v.24 no.2
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    • pp.112-118
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    • 2011
  • This paper introduces one type of prize collecting travelling salesman problem with time windows (PCTSPTW), proposes a mixed integer programming model for the problem, and shows that the problem can be reduced to the elementary shortest path problem with time windows and capacity constraints (ESPPTC). Then, a new dynamic programming algorithm is proposed to solve ESPPTC quickly. Computational results show the effectiveness of the proposed algorithm.

Development of Intelligent ATP System Using Genetic Algorithm (유전 알고리듬을 적용한 지능형 ATP 시스템 개발)

  • Kim, Tai-Young
    • Journal of Intelligence and Information Systems
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    • v.16 no.4
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    • pp.131-145
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    • 2010
  • The framework for making a coordinated decision for large-scale facilities has become an important issue in supply chain(SC) management research. The competitive business environment requires companies to continuously search for the ways to achieve high efficiency and lower operational costs. In the areas of production/distribution planning, many researchers and practitioners have developedand evaluated the deterministic models to coordinate important and interrelated logistic decisions such as capacity management, inventory allocation, and vehicle routing. They initially have investigated the various process of SC separately and later become more interested in such problems encompassing the whole SC system. The accurate quotation of ATP(Available-To-Promise) plays a very important role in enhancing customer satisfaction and fill rate maximization. The complexity for intelligent manufacturing system, which includes all the linkages among procurement, production, and distribution, makes the accurate quotation of ATP be a quite difficult job. In addition to, many researchers assumed ATP model with integer time. However, in industry practices, integer times are very rare and the model developed using integer times is therefore approximating the real system. Various alternative models for an ATP system with time lags have been developed and evaluated. In most cases, these models have assumed that the time lags are integer multiples of a unit time grid. However, integer time lags are very rare in practices, and therefore models developed using integer time lags only approximate real systems. The differences occurring by this approximation frequently result in significant accuracy degradations. To introduce the ATP model with time lags, we first introduce the dynamic production function. Hackman and Leachman's dynamic production function in initiated research directly related to the topic of this paper. They propose a modeling framework for a system with non-integer time lags and show how to apply the framework to a variety of systems including continues time series, manufacturing resource planning and critical path method. Their formulation requires no additional variables or constraints and is capable of representing real world systems more accurately. Previously, to cope with non-integer time lags, they usually model a concerned system either by rounding lags to the nearest integers or by subdividing the time grid to make the lags become integer multiples of the grid. But each approach has a critical weakness: the first approach underestimates, potentially leading to infeasibilities or overestimates lead times, potentially resulting in excessive work-inprocesses. The second approach drastically inflates the problem size. We consider an optimized ATP system with non-integer time lag in supply chain management. We focus on a worldwide headquarter, distribution centers, and manufacturing facilities are globally networked. We develop a mixed integer programming(MIP) model for ATP process, which has the definition of required data flow. The illustrative ATP module shows the proposed system is largely affected inSCM. The system we are concerned is composed of a multiple production facility with multiple products, multiple distribution centers and multiple customers. For the system, we consider an ATP scheduling and capacity allocationproblem. In this study, we proposed the model for the ATP system in SCM using the dynamic production function considering the non-integer time lags. The model is developed under the framework suitable for the non-integer lags and, therefore, is more accurate than the models we usually encounter. We developed intelligent ATP System for this model using genetic algorithm. We focus on a capacitated production planning and capacity allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using an evolutionary system to solve it efficiently. This method makes it possible for the population to reach the approximate solution easily. Moreover, we designed and utilized a representation scheme that allows the proposed models to represent real variables. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solutions converge to the optimum quickly.

An Optimization Model Based on Combining Possibility of Boundaries for Districting Problems (경계 결합 가능성 기반 구역설정 최적화 모델)

  • Kim, Kamyoung
    • Journal of the Korean Geographical Society
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    • v.49 no.3
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    • pp.423-437
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    • 2014
  • Districting is a spatial decision making process to make a new regional framework for affecting human activities. Natural barriers such as rivers and mountains located within a reorganized district may reduce the efficiency of reorganized human activities. This implies that it is necessary to consider boundary characteristics in a districting process. The purpose of this research is to develop a new spatial optimization model based on boundary characteristics for districting problems. The boundary characteristics are evaluated as continuous value expressing the possibility of combining adjacent two basic spatial units rather than a dichotomous value with 1 or 0 and are defined as an objective function in the model. In addition, the model has explicitly formulated contiguity constraints as well as constraints enforcing demand balance among districts such as population and area. The boundary attributes are categorized into physical and relational characteristics. Suitability analysis is used to combine various variables related to each boundary characteristic and to evaluate the coupling possibility between two neighboring basic units. The model is applied to an administrative redistricting problem. The analytical results demonstrate that various boundary characteristics could be modeled in terms of mixed integer programming (MIP).

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A Mathematical Model for Sewer Rehabilitation Planning by Considering Inflow/infiltration (불명수를 고려한 하수관거 정비 계획 수립을 위한 수학 모형)

  • Lee, Yong-Dae;Kim, Sheung-Kown;Kim, Jae-Hee;Kim, Joong-Hun
    • Journal of Korea Water Resources Association
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    • v.36 no.4
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    • pp.547-559
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    • 2003
  • In this study, a mathematical model is developed for sewer rehabilitation planning by considering cost and inflow/infiltration. A sewer rehabilitation planning model is required to decide the economic life of the sewer by considering trade-off between cost and inflow/infiltration. And it is required to find the optimal rehabilitation timing, according to the cost effectiveness of each sewer rehabilitation within the budget. To solve the problem, we formulated a multiple objective mixed integer programming(MOMIP) model based on network flow optimization. The network is composed of state nodes and arcs. The state nodes represent the remaining life and the arcs represent the change of the state. The model considers multiple objectives which are cost minimization and minimization of inflow/infiltration. Using the multiple objective optimization, the trade-off between the cost and inflow/infiltration is presented to the planner so that a proper sewer rehabilitation plan can be selected.

Development of Hedging Rule for Drought Management Policy Reflecting Risk Performance Criteria of Single Reservoir System (단일 저수지의 위험도 평가기준을 고려한 가뭄대비 Hedging Rule 개발)

  • Park, Myeong-Gi;Kim, Jae-Han;Jeong, Gwan-Su
    • Journal of Korea Water Resources Association
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    • v.35 no.5
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    • pp.501-510
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    • 2002
  • During drought or impending drought period, the reservoir operation method is required to incorporate demand-management policy rule. The objective of this study is focused to the development of demand reduction rule by incorporating hedging-effect for a single reservoir system. To improve the performance measure of the objective function and constraints, we could incorporate three risk performance criteria proposed by Hashimoto et al. (1982) by mixed-integer programming and also incorporate successive linear programming to overcome nonlinear hedging term from the previous study(Shih et al., 1994). To verify this model, this hedging rule was applied to the Daechung multi-purpose dam. As a result, we could evaluate optimal hedging parameters and monthly trigger volumes.

A Hybrid Heuristic Approach for Supply Chain Planningwith n Multi-Level Multi-Item Capacitated Lot Sizing Model (자원제약하의 다단계 다품목 공급사슬망 생산계획을 위한 휴리스틱 알고리즘)

  • Shin Hyun-Joon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.1
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    • pp.89-95
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    • 2006
  • Planning distributed manufacturing logistics is one of main issues in supply chain management. This paper proposes a hybrid heuristic approach for the Multi-Level, multi-item Capacitated Lot Sizing Problem (MLCLSP) in supply chain network. MLCLSP corresponds to a mixed integer programming (MIP) problem. With integer variable solutions determined by heuristic search, this MIP problem becomes linear program (LP). By repeatedly solving the relaxed MIP problems with a heuristic search method in a hybrid manner, this proposed approach allocates finite manufacturing resources fur each distributed facilities and generates feasible production plans. Meta heuristic search algorithm is presented to solve the MIP problems. The experimental test evaluates the computational performance under a variety of problem scenarios.

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Utilization of a Mathematical Programming Data Structure for the Implementation of a Water Resources Planning System (수자원 운영계획 시스템의 구현을 위한 수리계획 모형 자료구조의 활용)

  • Kim, Jae-Hee;Kim, Sheung-Kown;Park, Young-Joon
    • IE interfaces
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    • v.16 no.4
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    • pp.485-495
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    • 2003
  • This paper reports on the application of the integration of mathematical programming model and database in a decision support system (DSS) for the planning of the multi-reservoir operating system. The DSS is based on a multi-objective, mixed-integer goal programming (MIGP) model, which can generate efficient solutions via the weighted-sums method (WSM). The major concern of this study is seamless, efficient integration between the mathematical model and the database, because there are significant differences in structure and content between the data for a mathematical model and the data for a conventional database application. In order to load the external optimization results on the database, we developed a systematic way of naming variable/constraint so that a rapid identification of variables/constraints is possible. An efficient database structure for planning of the multi-reservoir operating system is presented by taking advantage of the naming convention of the variable/constraint.

A Mathematical Model for Optimal Communication Scheduling between Multiple Satellites and Multiple Ground Stations (다수의 인공위성-지상국 간 통신 스케줄 최적화 모형)

  • Jeong, Eugine;Kim, Heungseob
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.1
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    • pp.39-49
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    • 2018
  • In the satellite operation phase, a ground station should continuously monitor the status of the satellite and sends out a tasking order, and a satellite should transmit data acquired in the space to the Earth. Therefore, the communication between the satellites and the ground stations is essential. However, a satellite and a ground station located in a specific region on Earth can be connected for a limited time because the satellite is continuously orbiting the Earth, and the communication between satellites and ground stations is only possible on a one-to-one basis. That is, one satellite can not communicate with plural ground stations, and one ground station can communicate with plural satellites concurrently. For such reasons, the efficiency of the communication schedule directly affects the utilization of the satellites. Thus, in this research, considering aforementioned unique situations of spacial communication, the mixed integer programming (MIP) model for the optimal communication planning between multiple satellites and multiple ground stations (MS-MG) is proposed. Furthermore, some numerical experiments are performed to verify and validate the mathematical model. The practical example for them is constructed based on the information of existing satellites and ground stations. The communicable time slots between them were obtained by STK (System Tool Kit), which is a well known professional software for space flight simulation. In the MIP model for the MS-MG problems, the objective function is also considered the minimization of communication cost, and ILOG CPLEX software searches the optimal schedule. Furthermore, it is confirmed that this study can be applied to the location selection of the ground stations.

Adaptive Genetic Algorithm for the Manufacturing/Distribution Chain Planning

  • Kiyoung Shin;Chiung Moon;Kim, Yongchan;Kim, Jongsoo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.170-174
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    • 2003
  • In this research, we consider an integrated manufacturing/distribution planning problem in supply chain (SC) which has non-integer time lags. We focus on a capacitated manufacturing planning and capacity allocation problem for the system. We develop a mixed binary integer linear programming (MBLP) model and propose an efficient heuristic procedure using an adaptive genetic algorithm, which is composed of a regeneration procedure for evaluating infeasible chromosomes and the reduced costs from the LP-relaxation of the original model. The proposed an adaptive genetic algorithm was tested in terms of the solution accuracy and algorithm speed during numerical experiments. We found that our algorithm can generate the optimal solution within a reasonable computational time.

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