• Title/Summary/Keyword: Multi-objective Programming

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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.

Geometry optimization of a double-layered inertial reactive armor configured with rotating discs

  • Bekzat Ajan;Dichuan Zhang;Christos Spitas;Elias Abou Fakhr;Dongming Wei
    • Advances in Computational Design
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    • v.8 no.4
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    • pp.309-325
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    • 2023
  • An innovative inertial reactive armor is being developed through a multi-discipline project. Unlike the well-known explosive or non-explosive reactive armour that uses high-energy explosives or bulging effect, the proposed inertial reactive armour uses active disc elements that is set to rotate rapidly upon impact to effectively deflect and disrupt shaped charges and kinetic energy penetrators. The effectiveness of the proposed armour highly depends on the tangential velocity of the impact point on the rotating disc. However,for a single layer armour with an array of high-speed rotating discs, the tangential velocity is relatively low near the center of the disc and is not available between the gap of the discs. Therefore, it is necessary to configure the armor with double layers to increase the tangential velocity at the point of impact. This paper explores a multi-objective geometry design optimization for the double-layered armor using Nelder-Mead optimization algorithm and integration tools of the python programming language. The optimization objectives include maximizing both average tangential velocity and high tangential velocity areas and minimizing low tangential velocity area. The design parameters include the relative position (translation and rotation) of the disc element between two armor layers. The optimized design results in a significant increase of the average tangential velocity (38%), increase of the high tangential velocity area (71.3%), and decrease of the low tangential velocity area (86.2%) as comparing to the single layer armor.

GBNSGA Optimization Algorithm for Multi-mode Cognitive Radio Communication Systems (다중모드 Cognitive Radio 통신 시스템을 위한 GBNSGA 최적화 알고리즘)

  • Park, Jun-Su;Park, Soon-Kyu;Kim, Jin-Up;Kim, Hyung-Jung;Lee, Won-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.3C
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    • pp.314-322
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    • 2007
  • This paper proposes a new optimization algorithm named by GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm) which determines the best configuration for CR(Cognitive Radio) communication systems. Conventionally, in order to select the proper radio configuration, genetic algorithm has been introduced so as to alleviate computational burden along the execution of the cognition cycle proposed by Mitola. This paper proposes a novel optimization algorithm designated as GBNSGA for cognitive engine which can be described as a hybrid algorithm combining well-known Pareto-based NSGA(Non-dominated Sorting Genetic Algorithm) as well as GP(Goal Programming). By conducting computer simulations, it will be verified that the proposed method not only satisfies the user's service requirements in the form of goals. It reveals the fast optimization capability and more various solutions rather than conventional NSGA or weighted-sum approach.

Multi-floor Layout for the Liquefaction Process Systems of LNG FPSO Using the Optimization Technique (최적화 기법을 이용한 LNG FPSO 액화 공정 장비의 다층 배치)

  • Ku, Nam-Kug;Lee, Joon-Chae;Roh, Myung-Il;Hwang, Ji-Hyun;Lee, Kyu-Yeul
    • Journal of the Society of Naval Architects of Korea
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    • v.49 no.1
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    • pp.68-78
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    • 2012
  • A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.

The configuration Optimization of Truss Structure (트러스 구조물의 형상최적화에 관한 연구)

  • Lim, Youn Su;Choi, Byoung Han;Lee, Gyu Won
    • Journal of Korean Society of Steel Construction
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    • v.16 no.1 s.68
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    • pp.123-134
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    • 2004
  • In this research, a multilevel decomposition technique to enhance the efficiency of the configuration optimization of truss structures was proposed. On the first level, the nonlinear programming problem was formulated considering cross-sectional areas as design variables, weight, or volume as objective function and behavior under multiloading condition as design constraint. Said nonlinear programming problem was transformed into a sequential linear programming problem. which was effective in calculation through the approximation of member forces using behavior space approach. Such approach has proven to be efficient in sensitivity analysis and different form existing shape optimization studies. The modified method of feasible direction (MMFD) was used for the optimization process. On the second level, by treating only shape design variables, the optimum problem was transformed into and unconstrained optimal design problem. A unidirectional search technique was used. As numerical examples, some truss structures were applied to illustrate the applicability. and validity of the formulated algorithm.

An Integrated Model Using the Analytic Hierarchy Process and Linear Programming for the Supplier Selection (공급업체 선정을 위한 계층분석과정과 선형계획모형의 통합모형)

  • Kim, Shin-Joong
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.7
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    • pp.239-246
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    • 2008
  • The supplier selection has a direct effect on the organization's efficiency, effectiveness and competitiveness, so the right supplier selection is the most important decision of a company. In order to select the best suppliers, both qualitative and quantitative factors should be considered. To decide which suppliers are the best and how much should be purchased from each selected supplier, many models which considered a single objective and multiple objectives have been proposed. But they have problems in considering qualitative factors which are very important in supplier selection. So in this article an integration model of an analytical hierarchy process and linear programming is proposed to consider both qualitative and quantitative factors in choosing the best suppliers and placing the optimum order quantities among them. This integrated model can be applied effectively and easily any organization and management circumstances.

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Joint Optimization of Mobile Charging and Data Gathering for Wireless Rechargeable Sensor Networks

  • Tian, Xianzhong;He, Jiacun;Chen, Yuzhe;Li, Yanjun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.7
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    • pp.3412-3432
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    • 2019
  • Recent advances in radio frequency (RF) power transfer provide a promising technology to power sensor nodes. Adoption of mobile chargers to replenish the nodes' energy has recently attracted a lot of attention and the mobility assisted energy replenishment provides predictable and sustained power service. In this paper, we study the joint optimization of mobile charging and data gathering in sensor networks. A wireless multi-functional vehicle (WMV) is employed and periodically moves along specified trajectories, charge the sensors and gather the sensed data via one-hop communication. The objective of this paper is to maximize the uplink throughput by optimally allocating the time for the downlink wireless energy transfer by the WMV and the uplink transmissions of different sensors. We consider two scenarios where the WMV moves in a straight line and around a circle. By time discretization, the optimization problem is formulated as a 0-1 programming problem. We obtain the upper and lower bounds of the problem by converting the original 0-1 programming problem into a linear programming problem and then obtain the optimal solution by using branch and bound algorithm. We further prove that the network throughput is independent of the WMV's velocity under certain conditions. Performance of our proposed algorithm is evaluated through extensive simulations. The results validate the correctness of our proposed theorems and demonstrate that our algorithm outperforms two baseline algorithms in achieved throughput under different settings.

Optimization of Multi-reservoir Operation considering Water Demand Uncertainty in the Han River Basin (수요의 불확실성을 고려한 한강수계 댐 연계 운영 최적화)

  • Chung, Gun-Hui;Ryu, Gwan-Hyeong;Kim, Joong-Hoon
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.1
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    • pp.89-102
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    • 2010
  • Future uncertainty on water demand caused by future climate condition and water consumption leads a difficulty to determine the reservoir operation rule for supplying sufficient water to users. It is, thus, important to operate reservoirs not only for distributing enough water to users using the limited water resources but also for preventing floods and drought under the unknown future condition. In this study, the reservoir storage is determined in the first stage when future condition is unknown, and then, water distribution to users and river stream is optimized using the available water resources from the first stage decision using 2-stage stochastic linear programming (2-SLP). The objective function is to minimize the difference between target and actual water storage in reservoirs and the water shortage in users and river stream. Hedging rule defined by a precaution against severe drought by restricting outflow when reservoir storage decreases below a target, is also applied in the reservoir operation rule for improving the model applicability to the real system. The developed model is applied in a system with five reservoirs in the Han River basin, Korea to optimize the multi-reservoir system under various future water demand scenarios. Three multi-purposed dams - Chungju, Hoengseong, and Soyanggang - are considered in the model. Gwangdong and Hwacheon dams are also considered in the system due to the large capacity of the reservoirs, but they are primarily for water supply and power generation, respectively. As a result, the water demand of users and river stream are satisfied in most cases. The reservoirs are operated successfully to store enough water during the wet season for preparing the coming drought and also for reducing downstream flood risk. The developed model can provide an effective guideline of multi-reservoir operation rules in the basin.

유연성과 강성을 고려한 최적구조설계

  • Min, Seungjae;Nishiwaki, Shinji;Kikuchi, Noboru
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.9
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    • pp.1432-1440
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    • 1997
  • The flexibility as well as the stiffness is required to perform mechanical function of a structure such as compliant mechanisms, which can be applied to MEMS(Micro-Electro-Mechanical Systems), flexible manufacturing devices, and design for no assembly. In this paper, the optimal design problem to achieve both structural flexibility and stiffness is formulated using multi-objective function, and the optimization problem is resolved by using Finite Element Method(FEM) and Sequential Linear Programming(SLP). Design examples of compliant mechanisms are presented to validate the design method.

Machining Route Selection with Subcontracting Using Genetic Algorithm (와주를 고려한 가공경로 선정에서의 유전알고르즘 접근)

  • 이규용;문치웅;김재균
    • Korean Management Science Review
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    • v.17 no.2
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    • pp.55-65
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    • 2000
  • This paper addresses a problem of machining route selection in multi-stage process with machine group. This problem is considered the subcontracting and the production in-house such as regular and overtime work. the proposed model is formulated as a 0-1 integer programming constraining the avaliable time of each machine for planning period and total overtimes. The objective of the model is to minimize the sum of processing cost, overtime cost, and subcontracting cost. To solve this model, a genetic algorithm(GA) approach is developed. The effectiveness of the proposed GA approach is evaluated through comparisons with the optimal solution obtained from the branch and bound. In results, the same optimal solution is obtained from two methods at small size problem, and the consistent solution is provided by the GA approach at large size problem. The advantage of the GA approach is the flexibility into decision-making process because of providing multiple machining routes.

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