检索结果-内蒙古大学图书馆

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Resource allocation model and double-sphere crowding distance for evolutionary multi-objective optimization

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2014年第1期234卷 197-208页

作者： Lei, Yu Gong, Maoguo Zhang, Jun Li, Wei Jiao, Licheng Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ Xian 710071 Shaanxi Provinc Peoples R China

Convergence speed and diversity of nondominated solutions are two important performance indicators for multi-objective Evolutionary Algorithms (MOEAs). In this paper, we propose a Resource Allocation (RA) model based on Game Theory to accelerate the convergence speed of MOEAs, and a novel Double-Sphere Crowding Distance (DSCD) measure to improve the diversity of nondominated solutions. The mechanism of RA model is that the individuals in each group cooperate with each other to get maximum benefits for their group, and then individuals in the same group compete for private interests. The DSCD measure uses hyper-spheres consisting of nearest neighbors to estimate the crowding degree. Experimental results on convergence speed and diversity of nondominated solutions for benchmark problems and a real-world problem show the efficiency of these two proposed techniques. (C) 2013 Elsevier B.V. All rights reserved.

关键词： multi-objective programming Evolutionary computations Resource allocation Crowding distance

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization in uncertain random environments

引用

FUZZY OPTIMIZATION AND DECISION MAKING 2014年第4期13卷 397-413页

作者： Zhou, Jian Yang, Fan Wang, Ke Shanghai Univ Sch Management Shanghai 200444 Peoples R China

Uncertain random variables are used to describe the phenomenon of simultaneous appearance of both uncertainty and randomness in a complex system. For modeling multi-objective decision-making problems with uncertain random parameters, a class of uncertain random optimization is suggested for decision systems in this paper, called the uncertain random multi-objective programming. For solving the uncertain random programming, some notions of the Pareto solutions and the compromise solutions as well as two compromise models are defined. Subsequently, some properties of these models are investigated, and then two equivalent deterministic mathematical programming models under some particular conditions are presented. Some numerical examples are also given for illustration.

关键词： multi-objective optimization multi-objective programming Uncertain random variable Uncertain random programming Uncertainty theory

来源：评论

学校读者我要写书评

暂无评论

BANK BALANCE-SHEET MANAGEMENT - AN ALTERNATIVE multi-objective MODEL

引用

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 1988年第4期39卷 401-410页

作者： TAYI, GK LEONARD, PA School of Business State University of New York at Albany USA

Bank balance-sheet management entails considering competing and conflicting objectives such as maximization of returns and minimization of risks associated with alternative portfolio combinations. Traditional multi-objective models simply provide the decision-maker with the entire set of non-dominated solutions; the decision-maker must then choose, unaided, the best solution based on his subjective trade-offs, experience and judgement. This paper develops an alternative multi-objective balance-sheet management model which allows the explicit incorporation of the decision-maker's trade-offs between conflicting objectives, and attempts to reduce his cognitive burden while ensuring that the solution obtained belongs to the set of non-dominated points.

关键词： banking multi-objective programming

来源：评论

学校读者我要写书评

暂无评论

Optimal allocation of regional water resources based on multi-objective dynamic equilibrium strategy

引用

APPLIED MATHEMATICAL MODELLING 2021年 90卷 1183-1203页

作者： Feng, Jianghong Jinan Univ Sch Management 601 Huangpu Ave West Guangzhou Peoples R China

Raising water demand, insufficient freshwater resources and uneven precipitation are the main causes of water conflicts in the river basin. The main challenges in water resources allocation are the following: first, the uncertainty of water supply caused by climate change;second, the dynamic allocation of water resources is not considered;third, there is a lack of equitable water allocation, which may lead to intensified conflicts among the water user sectors. Based on the above challenges, a multi-objective dynamic programming optimal water resources allocation model under uncertainties is established in this paper, which could be a resolution for water disputes as it addresses simultaneously economic, social and environmental benefits. The proposed model considers maximizing the minimum satisfaction degree of each water sector, maximizing the utilization efficiency of water resources in the basin, and maximizing economic benefits. Satisfaction degree function is introduced to optimize water allocation equality in water use sectors (agricultural, domestic, and industrial sectors), and economic efficiency loss acceptance is integrated into the model constraints to control the economic loss corresponding to variations in water availability. In addition, a case study demonstrated the practicality and rationality of the proposed model, and the model results proposed herein show significantly help for a single river basin. Most importantly, the results show that model with dynamic constraint ensures a greater overall economic return for the entire basin, and a larger variation in water resources of sub-area leads to a larger maximum economic efficiency loss. Moreover, the proposed model herein is flexible and can be used in other developing countries/regions only by modifying the parameters according to the actual situation. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Water allocation multi-objective programming Satisfaction degree Economic benefit multi-stage decision

来源：评论

学校读者我要写书评

暂无评论

A general reverse logistics network design model for product reuse and recycling with environmental considerations

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2016年第9-12期87卷 2693-2711页

作者： Yu, Hao Solvang, Wei Deng UiT Arctic Univ Norway Fac Engn Sci & Technol Dept Ind Engn Narvik Nordland Norway

Reverse logistics is believed to be one of the most promising solutions for capturing the remaining values from used products and has been extensively focused by both academics and practitioners during the past two decades. Conceptual framework, mathematical programming, and computational algorithms have been developed for decision-making at strategic, tactical, and operational levels of a reverse supply chain. In this paper, a novel idea for the design and planning of a general reverse logistics network is suggested and formulated through multi-objective mixed integer programming. The reverse logistics system is an independent network and comprises of three echelons for collection, remanufacturing, recycling, energy recovery, and disposal of used products. The mathematical model not only takes into account the minimization of system operating costs, but also considers minimization of carbon emissions related to the transportation and processing of used products, and the minimum rate of resource utilization is also required in order to minimize the waste of resources in landfill. Illustration, sensitivity analysis, and numerical experimentation are given to show the applicability and computational efficiency of the proposed model. This work provides an alternative approach to account both economic and environmental sustainability of a reverse logistics system. The result explicitly shows the trade-off between the costs and carbon emissions, cost effectiveness for improving environmental performance, and influences from resource utilization, all of which have great practical implication on decision-making of network configurations and transportation planning of a reverse logistics system. For future development of this work, suggestions are also given latter in this paper.

关键词： Reverse logistics Network design Facility location Transportation planning Environmental impacts Carbon emissions multi-objective programming Mixed integer programming

来源：评论

学校读者我要写书评

暂无评论

On the increasing importance of multiple criteria decision aid methods for portfolio selection

引用

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2018年第10期69卷 1525-1542页

作者： Aouni, Belaid Doumpos, Michalis Perez-Gladish, Blanca Steuer, Ralph E. Qatar Univ Coll Business & Econ Doha Qatar Tech Univ Crete Sch Prod Engn & Management Financial Engn Lab Univ Campus Khania Greece Univ Oviedo Dept Quantitat Econ Fac Econ & Business Asturias Spain Univ Georgia Dept Finance Athens GA 30602 USA

In 1952, Markowitz published his famous paper on portfolio selection that transformed the field of finance. Although over 65 years have passed since then, the mean-variance model remains today the predominant model in portfolio selection. Having endured many criticisms over this period, the one that has perhaps been the most persistent is the fact that mainstream mean-variance theory is unable to accommodate additional criteria beyond expected return and variance. With investment decision-making having become more complex, this is a real problem as many problems with additional criteria exist and are only increasing in number and importance. In this paper, we review the papers that have been published that apply methods and procedures in an exact (as opposed to evolutionary) sense to address problems in portfolio selection with criteria beyond mean and variance. We also analyse the methodologies that allow the solution of the problem in a multiple criteria context, thus extending the features of the mean-variance approach that have caused portfolio theory to have such impact.

关键词： multiple criteria decision aid multi-objective programming portfolio selection security selection portfolio optimisation

来源：评论

学校读者我要写书评

暂无评论

A minimax regret approach for robust multi-objective portfolio selection problems with ellipsoidal uncertainty sets

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2020年 147卷 106646-106646页

作者： Li, Jun Wang, Lishuai Univ Elect Sci & Technol China Sch Management & Econ Chengdu 610054 Peoples R China

Since security return cannot be accurately estimated using past data, in this paper it is assumed to take values in a given ellipsoidal uncertainty set. This paper aims to discuss a robust multi-objective portfolio selection problem based on the minimax regret criterion under an ellipsoidal uncertainty sets, in which the two objective functions are the portfolio return to be maximized and the mean absolute deviation as a risk measure to be minimized. The robust counterpart formulation for the proposed model is firstly presented, then an algorithm based on the relaxation procedure is designed to solve the robust counterpart formulation with second-order cone constraints and infinite constraints. Finally, a practical example based on real market data is presented to illustrate the effectiveness of the proposed model and the algorithm. Compared with the traditional robust portfolio model based on minimax robustness, the robust minimax regret optimal solutions proposed in this paper have better performance on several evaluation criteria.

关键词： Robust optimization multi-objective programming Minimax regret Ellipsoidal uncertainty Portfolio optimization

来源：评论

学校读者我要写书评

暂无评论

Single- and multi-objective defensive location problems on a network

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2008年第1期188卷 76-84页

作者： Uno, Takeshi Katagiri, Hideki Hiroshima Univ Grad Sch Engn Higashihiroshima 7398527 Japan

This paper considers a new optimal location problem, called defensive location problem (DLP). In the DLPs, a decision maker locates defensive facilities in order to prevent her/his enemies from reaching an important site, called a core;for example, "a government of a country locates self-defense bases in order to prevent her/his aggressors from reaching the capital of the country." It is assumed that the region where the decision maker locates her/his defensive facilities is represented as a network and the core is a vertex in the network, and that the facility locater and her/his enemy are an upper and a lower level of decision maker, respectively. Then the DLPs are formulated as bilevel 0-1 programming problems to find Stackelberg solutions. In order to solve the DLPs efficiently, a solving algorithm for the DLPs based upon tabu search methods is proposed. The efficiency of the proposed solving methods is shown by applying to examples of the DLPs. Moreover, the DLPs are extended to multi-objective DLPs that the decision maker needs to defend several cores simultaneously. Such DLPs are formulated as multi-objective programming problems. In order to find a satisfying solution of the decision maker for the multi-objective DLP, an interactive fuzzy satisfying method is proposed, and the results of applying the method to examples of the multi-objective DLPs are shown. (C) 2007 Elsevier B.V. All rights reserved.

关键词： facility location bilevel programming Stackelberg solution Tabu search multi-objective programming interactive fuzzy satisfying method

来源：评论

学校读者我要写书评

暂无评论

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

引用

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)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：