• Title/Summary/Keyword: Multiple objective function

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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.

A Study on the Allocation and Engagement Scheduling of Air Defense Missiles by Using Mixed Integer Programming (혼합정수계획법을 이용한 요격미사일의 할당 및 교전 일정계획에 관한 연구)

  • Lee, Dae Ryeock;Yang, Jaehwan
    • Korean Management Science Review
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    • v.32 no.4
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    • pp.109-133
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    • 2015
  • This paper considers the allocation and engagement scheduling of air defense missiles by using MIP (mixed integer programming). Specifically, it focuses on developing a realistic MIP model for a real battle situation where multiple enemy missiles are headed toward valuable defended assets and there exist multiple air defense missiles to counteract the threats. In addition to the conventional objective such as the minimization of surviving target value, the maximization of total intercept altitude is introduced as a new objective. The intercept altitude of incoming missiles is important in order to minimize damages from debris of the intercepted missiles and moreover it can be critical if the enemy warhead contains an atomic or chemical bomb. The concept of so called the time window is used to model the engagement situation and a continuous time is assumed for flying times of the both missiles. Lastly, the model is extended to simulate the situation where the guidance radar, which guides a defense missile to its target, has the maximum guidance capacity. The initial mathematical model developed contains several non-linear constraints and a non-linear objective function. Hence, the linearization of those terms is performed before it is solved by a commercially available software. Then to thoroughly examine the MIP model, the model is empirically evaluated with several test problems. Specifically, the models with different objective functions are compared and several battle scenarios are generated to evaluate performance of the models including the extended one. The results indicate that the new model consistently presents better and more realistic results than the compared models.

Approximate Multi-Objective Optimization of Robot Casting Considering Deflection and Weight (처짐과 무게를 고려한 주물 프레임의 다중목적 근사최적설계)

  • Choi, Ha-Young;Lee, Jongsoo;Park, Juno
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.21 no.6
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    • pp.954-960
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    • 2012
  • Nowadays, rapidly changing and unstable global economic environments request a lot of roles to engineers. In this situation, product should be designed to make more profit by cost down and to satisfy distinguished performance comparing to other competitive ones. In this research, the optimization design of the industrial robot casting will be done. The weight and deflection have to be reduced as objective functions and stress has to be constrained under some constant value. To reduce time cost, CCD (Central Composite Design) will be used to make experimental design. And RSM (Response Surface Methodology) will be taken to make regression model for objective functions and constraint function. Finally, optimization will be done with Genetic Algorithm. In this problem, the objective functions are multiple, so NSGA-II which is brilliant and efficient for such a problem will be used. For the solution quality check, the diversity between Pareto solutions will be also checked.

Multiobjective Optimization of Three-Stage Spur Gear Reduction Units Using Interactive Physical Programming

  • Huang Hong Zhong;Tian Zhi Gang;Zuo Ming J.
    • Journal of Mechanical Science and Technology
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    • v.19 no.5
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    • pp.1080-1086
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    • 2005
  • The preliminary design optimization of multi-stage spur gear reduction units has been a subject of considerable interest, since many high-performance power transmission applications (e.g., automotive and aerospace) require high-performance gear reduction units. There are multiple objectives in the optimal design of multi-stage spur gear reduction unit, such as minimizing the volume and maximizing the surface fatigue life. It is reasonable to formulate the design of spur gear reduction unit as a multi-objective optimization problem, and find an appropriate approach to solve it. In this paper an interactive physical programming approach is developed to place physical programming into an interactive framework in a natural way. Class functions, which are used to represent the designer's preferences on design objectives, are fixed during the interactive physical programming procedure. After a Pareto solution is generated, a preference offset is added into the class function of each objective based on whether the designer would like to improve this objective or sacrifice the objective so as to improve other objectives. The preference offsets are adjusted during the interactive physical programming procedure, and an optimal solution that satisfies the designer's preferences is supposed to be obtained by the end of the procedure. An optimization problem of three-stage spur gear reduction unit is given to illustrate the effectiveness of the proposed approach.

Identification of isotropic and orthotropic constitutive parameters by FEA-free energy-based inverse characterization method

  • Shang, Shen;Yun, Gun Jin;Kunchum, Shilpa;Carletta, Joan
    • Structural Engineering and Mechanics
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    • v.45 no.4
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    • pp.471-494
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    • 2013
  • In this paper, identification of isotropic and orthotropic linear elastic material constitutive parameters has been demonstrated by a FEA-free energy-based inverse analysis method. An important feature of the proposed method is that it requires no finite element (FE) simulation of the tested material. Full-field displacements calculated using digital image correlation (DIC) are used to compute DIC stress fields enforcing the equilibrium condition and DIC strain fields using interpolation functions. Boundary tractions and displacements are implicitly recast into an objective function that measures the energy residual of external work and internal elastic strain energy. The energy conservation principle states that the residual should be zero, and so minimizing this objective function inversely identifies the constitutive parameters. Synthetic data from simulated testing of isotropic materials and orthotropic composite materials under 2D plane stress conditions are used for verification of the proposed method. When identifying the constitutive parameters, it is beneficial to apply loadings in multiple directions, and in ways that create non-uniform stress distributions. The sensitivity of the parameter identification method to noise in both the measured full-field DIC displacements and loadings has been investigated.

Small Base Station Association and Cooperative Receiver Design for HetNets via Distributed SOCP

  • Lu, Li;Wang, Desheng;Zhao, Hongyi;Liu, Yingzhuang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.12
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    • pp.5212-5230
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    • 2016
  • How to determine the right number of small base stations to activate in multi-cell uplinks to match traffic from a fixed quantity of K users is an open question. This paper analyses the uplink cooperative that jointly receives base stations activation to explore this question. This paper is different from existing works only consider transmitting power as optimization objective function. The global objective function is formulated as a summation of two terms: transmitting power for data and coordinated overhead for control. Then, the joint base stations activation and beamforming problem is formulated as a mixed integer second order cone optimization. To solve this problem, we develop two polynomial-time distributed methods. Method one is a two-stage solution which activates no more than K small base stations (SBSs). Method two is a heuristic algorithm by dual decomposition to MI-SOCP that activates more SBSs to obtain multiple-antennae diversity gains. Thanks to the parallel computation for each node, our methods are more computationally efficient. The strengths and weaknesses of these two proposed two algorithms are also compared using numerical results.

The Multiple Traveling Purchaser Problem for Minimizing the Maximal Acquisition Completion Time in Wartime (전시 최장 획득완료시간 최소화를 위한 복수 순회구매자 문제)

  • Choi, Myung-Jin;Moon, Woo-Bum;Choi, Jin-Ho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.3
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    • pp.458-466
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    • 2011
  • In war time, minimizing the logistics response time for supporting military operations is strongly needed. In this paper, i propose the mathematical formulation for minimizing the maximal acquisition completion time in wartime or during a state of emergency. The main structure of this formulation is based on the traveling purchaser problem (TPP), which is a generalized form of the well-known traveling salesman problem (TSP). In the case of the general TPP, an objective function is to minimize the sum of the traveling cost and the purchase cost. However, in this study, the objective function is to minimize the traveling cost only. That's why it's more important to minimize the traveling cost (time or distance) than the purchase cost in wartime or in a state of emergency. I generate a specific instance and find out the optimal solution of this instance by using ILOG OPL STUDIO (CPLEX version 11.1).

A Study on Hydrophone Array Design Optimization for Cavitation Tunnel Noise Measurements (캐비테이션 터널 시험용 청음기배열 최적 설계기법)

  • Park, Cheolsoo;Seol, Hanshin;Kim, Gundo;Park, Youngha
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.3
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    • pp.237-246
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    • 2013
  • This paper proposes a hydrophone array design optimization technique for cavitation tunnel noise measurements. The optimization technique comprises of design parameters, an objective function and an optimization algorithm. The design parameters are defined for circular, spiral and multi-spiral arrays. The objective function is defined so as to consider the mainlobe beamwidth and the maximum sidelobe level simultaneously. A global optimization scheme is applied to the array design using very fast simulated reannealing (VFSR). After applying the optimization technique to arrays respectively, the peak sidelobe level and the mainlobe beamwidth of optimum arrays are analyzed. Finally the array patterns considering multiple reflections in the cavitation tunnel are evaluated to validate the proposed method.

Model updating and damage detection in multi-story shear frames using Salp Swarm Algorithm

  • Ghannadi, Parsa;Kourehli, Seyed Sina
    • Earthquakes and Structures
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    • v.17 no.1
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    • pp.63-73
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    • 2019
  • This paper studies damage detection as an optimization problem. A new objective function based on changes in natural frequencies, and Natural Frequency Vector Assurance Criterion (NFVAC) was developed. Due to their easy and fast acquisition, natural frequencies were utilized to detect structural damages. Moreover, they are sensitive to stiffness reduction. The method presented here consists of two stages. Firstly, Finite Element Model (FEM) is updated. Secondly, damage severities and locations are determined. To minimize the proposed objective function, a new bio-inspired optimization algorithm called salp swarm was employed. Efficiency of the method presented here is validated by three experimental examples. The first example relates to three-story shear frame with two single damage cases in the first story. The second relates to a five-story shear frame with single and multiple damage cases in the first and third stories. The last one relates to a large-scale eight-story shear frame with minor damage case in the first and third stories. Moreover, the performance of Salp Swarm Algorithm (SSA) was compared with Particle Swarm Optimization (PSO). The results show that better accuracy is obtained using SSA than using PSO. The obtained results clearly indicate that the proposed method can be used to determine accurately and efficiently both damage location and severity in multi-story shear frames.

On the Need for Efficient Load Balancing in Large-scale RPL Networks with Multi-Sink Topologies

  • Abdullah, Maram;Alsukayti, Ibrahim;Alreshoodi, Mohammed
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.212-218
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    • 2021
  • Low-power and Lossy Networks (LLNs) have become the common network infrastructure for a wide scope of Internet of Things (IoT) applications. For efficient routing in LLNs, IETF provides a standard solution, namely the IPv6 Routing Protocol for LLNs (RPL). It enables effective interconnectivity with IP networks and flexibly can meet the different application requirements of IoT deployments. However, it still suffers from different open issues, particularly in large-scale setups. These include the node unreachability problem which leads to increasing routing losses at RPL sink nodes. It is a result of the event of memory overflow at LLNs devices due to their limited hardware capabilities. Although this can be alleviated by the establishment of multi-sink topologies, RPL still lacks the support for effective load balancing among multiple sinks. In this paper, we address the need for an efficient multi-sink load balancing solution to enhance the performance of PRL in large-scale scenarios and alleviate the node unreachability problem. We propose a new RPL objective function, Multi-Sink Load Balancing Objective Function (MSLBOF), and introduce the Memory Utilization metrics. MSLBOF enables each RPL node to perform optimal sink selection in a way that insure better memory utilization and effective load balancing. Evaluation results demonstrate the efficiency of MSLBOF in decreasing packet loss and enhancing network stability, compared to MRHOF in standard RPL.