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2016 International Conference on Applied Mathematics, Simulation and Modelling(AMSM2016)

作者： Hong Fang Xinglong Ren College of Science Huazhong Agricultural University

ISBN: (纸本)9781510833890

It is of great necessity to explore a method to seek for a wrecked plane in the sea. In this paper we think of a static situation and establish a model that can be applied to quickly search the plane fallen into different oceans. Firstly, we develop a parabola model to simulate the process of plane falling. Take the projection of where the plane finally signaled on the sea as the center, and the distance between the two signaling positions plus the horizontal distance of the parabolic movement as radius, we can initially define the most likely falling area. Secondly, we apply Kruskal minimal spanning tree algorithm to minimize the total searching route. Then we regard suspicious neighboring goals as a single zone in different ways and each plane searches only one zone. Considering time cost and fuel cost, a multiobjective programming model is established to optimize the searching scheme. Finally we obtain the minimum cost and time for the whole searching.

关键词： district division multi-objective programming Kruskal minimum spanning tree

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Design of the Optimization Scheme about the Vehicle logistics Loading

Design of the Optimization Scheme about the Vehicle logistic...

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第28届中国控制与决策会议

作者： Jie Zhang Yang Lei Yang Yu College of Science Northeast Dianli University Northeast Dianli University

ISBN: (纸本)9781467397155

In order to achieve the minimum amount of car carriers and the shortest driving path,this paper analyzes the actual constraints that passenger cars loading need to satisfy,and then builds the multi-objective integer programming model of the design of the optimization scheme about passenger cars logistics loading and it also designs a heuristic algorithm of the problem,which are all used to solve practical problems.

关键词： Passenger Cars Logistics multi-objective programming Integer programming Heuristic Algorithm

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An improved version of a core based algorithm for the multi-objective multi-dimensional knapsack problem: A computational study and comparison with meta-heuristics

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APPLIED MATHEMATICS AND COMPUTATION 2015年 270卷 25-43页

作者： Mavrotas, George Florios, Kostas Figueira, Jose Rui Natl Tech Univ Athens Sch Chem Engn Lab Ind & Energy Econ GR-10682 Athens Greece Athens Univ Econ & Business Dept Stat Athens Greece Univ Nova Lisboa Inst Super Tecn CEG IST P-1200 Lisbon Portugal

In this paper we propose an improved version of a core based algorithm for the multi-objective extension of one of the most well-known combinatorial optimization problems, the multidimensional knapsack problem. The original algorithm was designed only for bi-objective problems combining an extension of the core concept and a branch-and-bound algorithm. It is a deterministic algorithm and the core concept exploits the "divide and conquer" solution strategy which proves very effective in such problems. The new version is not limited to bi-objective problems;it can effectively handle problems with more than two objective functions and it has features that greatly accelerate the solution process. Namely, these features are the use of a heuristic based on the Dantzig bound in the fathoming process and the better housekeeping of the incumbent list through filtering of solutions. The key parameters of the new algorithm are (a) the size of the core and (b) the number of provided cores. Varying these parameters the user can easily tune the size of the obtained Pareto set. A comparison with evolutionary algorithms, like NSGA II, SPEA2 and MOEA/D, has been made according to run time and the most widely used metrics (set coverage, set convergence etc). Our new version performs better than the most popular evolutionary algorithms and it is comparable to very recent state-of-the-art metaheuristics, like multi-objective Memetic Algorithm based on Decomposition (MOMAD), for multi-objective programming. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Combinatorial optimization Branch-and-bound Evolutionary computations Metaheuristics multi-objective programming multi-dimensional knapsack problems

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A two-stage method for member selection of emergency medical service

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2015年第4期30卷 871-891页

作者： Chen, Xi Fan, Zhiping Li, Zhiwu Han, Xueliang Zhang, Xiao Jia, Haochen Xidian Univ Sch Econ & Management Xian 710071 Peoples R China Northeastern Univ Sch Business Adm Shenyang 110819 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Macau 999078 Taipa Peoples R China King Abdulaziz Univ Fac Engn Jidda 21589 Saudi Arabia Xidian Univ Sch Electromech Engn Xian 710071 Peoples R China SUNY Stony Brook Coll Arts & Sci Stony Brook NY 11790 USA

Member selection is an important decision making problem in the formation of emergency medical teams. It involves selecting an optimal combination from a reasonable number of doctors, nurses and emergency medical technicians. Selecting suitable members for a medical emergency team (MET) will facilitate the effectiveness of emergency medical service (EMS). Essentially, investigations on EMS could offer models which increase the efficiency of proper matching and earn time to save lives. The existing methods for member selection pay much attention to the individual information to measure the individual performance of members, while few studies focus on the collaborative information to measure the collaborative performance between members. This paper aims to propose a two-stage method for member selection of an MET. In the first stage, knowledge rules are proposed to identify the valid candidates quickly. In the second stage, the individual information of members, the collaborative information between members, and the response time of EMS are all considered to build a three-objective 0-1 programming model. Due to its intractability, the model is solved by a non-dominated sorting genetic algorithm II. Liberia, now suffering the Ebola virus, is used as a backdrop for this study. A practical example followed by a computational simulation experiment is used to illustrate the applicability and the effectiveness of the proposed method.

关键词： Emergency medical service (EMS) Member selection multi-objective programming Non-dominated sorting genetic algorithm II (NSGA-II)

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Comment on "A hybrid multi-objective cultural algorithm for short-term environmental/economic hydrothermal scheduling" by Lu et al. [Energy Convers. Manage. 52 (2011) 2121-2134]

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ENERGY CONVERSION AND MANAGEMENT 2015年 99卷 414-417页

作者： Ahmadi, Abdollah Nezhad, Ali Esmaeel Heidari, Alireza Agelidis, Vassilios G. Univ New S Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Islamic Azad Univ Marvdasht Branch Dept Elect Engn Marvdasht Iran

This paper aims to discuss the short-term hydrothermal scheduling problem [Energy Convers. Manage. 52 (2011) 2121-2134], while a Hybrid multi-objective Cultural Algorithm (HMOCA) has been employed to solve the presented problem. This problem has been proposed in a multi-objective framework with fuel cost and emission of thermal units as two objective functions aimed to be minimized, simultaneously. However, there are some inaccuracies made by the authors in the mentioned reference, while presenting the solutions. In this regard, the results obtained for the water discharge rate of hydro units and accordingly, the optimal values derived for the power produced by such units are inaccurate and must be corrected for the optimal hydrothermal scheduling. Therefore, the present paper first highlights these inaccuracies and afterwards, epsilon-constraint technique and lexicographic optimization are used to propose the correct solutions. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Hybrid multi-objective Cultural Algorithm Hydrothermal scheduling multi-objective programming Epsilon-constraint technique

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A decision aided system for sustainable waste management

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2015年第1期9卷 29-40页

作者： Yu, Hao Solvang, Wei Deng Yuan, Song Yang, Yong Narvik Univ Coll Dept Ind Engn PO 385 Lodve Langes Gate 2 N-8505 Narvik Norway China Urban Construct Design & Res Inst Beijing Peoples R China Zhejiang Gongshang Univ Sch Stat & Math Hangzhou Zhejiang Peoples R China

Nowadays, sustainable development has increasingly drawing public attention due to environmental, economic and social reasons. To pursue a more competitive and sustainable society needs greater concentration on waste management. However, waste management is a worldwide challenge, because several interactive influencing factors, i.e., costs, risks, equity, etc., and the characteristics of different regions have to be simultaneously taken into consideration. The optimal solution for one influencing factor is usually not a good choice for another. Therefore, it is highly preferred to develop a sophisticated system analysing tool for managing those interactive influencing factors as well as the characteristics of different waste management systems in an efficient and sustainable manner. In this paper, a decision aided system based upon multi-objective programming is proposed for addressing the optimal trade-off among costs, risks and sustainability of waste management system from long-term perspective. A theoretical framework of sustainable waste management is first established, and the mathematical model as well as the computation method is then formulated accordingly. To present the application of this model, an illustrative calculation is performed as well, and the model computation in this paper is done by using programming language in a professional optimization software Lingo 13.0.

关键词： Decision aided system multi-objective programming sustainable waste management

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Optimization of China Crude Oil Transportation Network with Genetic Ant Colony Algorithm

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INFORMATION 2015年第3期6卷 467-480页

作者： Wang, Yao Lu, Jing Dalian Maritime Univ Transportat Management Coll Dalian 116026 Liaoning Peoples R China

Taking into consideration both shipping and pipeline transport, this paper first analysed the risk factors for different modes of crude oil import transportation. Then, based on the minimum of both transportation cost and overall risk, a multi-objective programming model was established to optimize the transportation network of crude oil import, and the genetic algorithm and ant colony algorithm were employed to solve the problem. The optimized result shows that VLCC (Very Large Crude Carrier) is superior in long distance sea transportation, whereas pipeline transport is more secure than sea transport. Finally, this paper provides related safeguard suggestions on crude oil import transportation.

关键词： integrated transportation transportation safety multi-objective programming crude oil import transportation network

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Decision Support System and multi-Criteria Decision Aid: A State of the Art and Perspectives

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JOURNAL OF multi-CRITERIA DECISION ANALYSIS 2015年第1-2期22卷 101-117页

作者： Razmak, Jamil Aouni, Belaid Laurentian Univ Sudbury ON P3E 2C6 Canada Qatar Univ Coll Business & Econ Dept Management & Mkt POB 2713 Doha Qatar

The aim of this paper is to highlight the role of the Decision Support System within the field of multi-criteria decision aid (MCDA). The MCDA tools have been incorporated into systems to create multi-Criteria Decision Support Systems (MCDSSs). In our literature review, we noticed that more than 100 papers have been written over a 20-year period in which MCDSS was used as a decision-making tool. The present paper describes some real applications of MCDSS in different fields, harmoniously combined with decision-making methods such as analytic hierarchy process, Utility Additive, and Goal programming. The present study proposes an integrative MCDSS evaluation through guidance on the tools most useful for a specific user with a particular decision problem. Copyright (C) 2014 John Wiley & Sons, Ltd.

关键词： Decision Support System multi-Criteria Decision Aid multi-objective programming Typology

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A Recommender System for the Optimal Combination of Energy Resources with Cost-benefit Analysis 5

A Recommender System for the Optimal Combination of Energy R...

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2015 International Conference on Industrial Engineering and Operations Management (IEOM)

作者： Kung, Li Wang, Hsiao-Fan Natl Tsing Hua Univ Dept Ind Engn & Engn Management Hsinchu 30013 Taiwan

ISBN: (纸本)9781479960651

Owing to the over-exploitation of fossil fuels, many governments have been promoting renewable energy to resolve the limitation of fossil energy and environmental problems. Nevertheless, most of the electricity data lack of systematic analysis to provide useful information. Furthermore, due to the development of cloud technology, these big data vary in type and time. Without appropriate big data analysis and user interface, data would provide error messages. Besides, few of the websites are built for enterprise to provide suggestion as a recommender. In summary, this study intends to develop a recommender system including cloud data base, analytical module and user interface. Based on continuous Markov chain, we analyze data according to the historical electricity data;through time series analysis and multi-objective programming models, a long-term investment of renewable energy decision supports and the best combination of renewable energy can be revealed. The research integrates these modules to construct an enterprise-oriented cloud system. To ensure the effectiveness of the platform, validation test will be performed. The result demonstrates that the recommender system can be used to assist the company in making the best investment of renewable energy and the best combination of energy consumption.

关键词： Big data analysis user interface continuous Markov chain multi-objective programming decision support

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A METHOD TO FUZZY multi-objective PROBLEMS UNDER RANDOM ENVIRONMENT 14

A METHOD TO FUZZY MULTI-OBJECTIVE PROBLEMS UNDER RANDOM ENVI...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Tsang, Eric C. C. Jie, Jing-Duo Jin, Chen-Xia Macao Univ Sci & Technol Fac Informat Technol Macau Peoples R China Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050018 Peoples R China

ISBN: (纸本)9781467372206

Randomness and fuzziness are two common uncertainties in decision process, and they always coexist in many real multi-objective problems such as resources allocation, complex system optimization. So it is a widespread research content on the process problem of the two uncertainties in academic and application fields. In this paper, aimed at the multi-objective programming with fuzzy goals and random coefficients, we first propose the level effect function and construct the effect probability of fuzzy events by regarding the fuzzy goals as the fuzzy events. Then we discuss the probability of fuzzy number and the probability formulas of several special fuzzy events are further given. Besides, we establish the multi-objective programming maximum effect probability model (abbreviated as MOP-MEP model). Finally, we illustrate the validity of MOP-MEP model in combination with a case.

关键词： multi-objective programming Effect probability Fuzzy event Random environment decision making

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