检索结果-内蒙古大学图书馆

Solving the bi-objective prize-collecting Steiner tree problem with the ε-constraint method

Electronic Notes in Discrete Mathematics 2013年 41卷 181-188页

作者： Leitner, Markus Ljubić, Ivana Sinnl, Markus Institute of Computer Graphics and Algorithms Vienna University of Technology Vienna Austria Department of Statistics and Operations Research University of Vienna Vienna Austria

In this paper, we study the bi-objective prize-collecting Steiner tree problem, whose goal is to find a subtree that minimizes the edge costs for building that tree, and, at the same time, to maximize the collected node revenues. We propose to solve the problem using an ε-constraint algorithm. This is an iterative mixed-integer-programming framework that identifies one solution for every point on the Pareto front. In this framework, a branch-and-cut approach for the single-objective variant of the problem is enhanced with warm-start procedures that are used to (i) generate feasible solutions, (ii) generate violated cutting planes, and (iii) guide the branching process. Standard benchmark instances from the literature are used to assess the efficacy of our method. © 2013 Elsevier B.V.

关键词： ε-constraint method Bi-objective combinatorial optimization Steiner tree problem

来源：评论

学校读者我要写书评

暂无评论

Learning Non-Negativity Constrained Variation for Image Denoising and Deblurring

引用

高等学校计算数学学报（英文版） 2017年第4期10卷 852-871页

作者： Tengda Wei Linshan Wang Ping Lin Jialing Chen Yangfan Wang Haiyong Zheng College of Oceanic and Atmospheric Sciences Ocean University of China Qingdao 266100 China College of Mathematics Ocean University of China Qingdao 266100 China Department of Mathematics University of Dundee Dundee DD1 4HN UK College of Marine Life Science Ocean University of China Qingdao 266100China College of Information Science and Engineering Ocean University of ChinaQingdao 266100 China

This paper presents a heuristic Learning-based Non-Negativity Constrained Variation (L-NNCV) aiming to search the coefficients of variational model automatically and make the variation adapt different images and problems by supervised-learning *** model includes two terms:a problem-based term that is derived from the prior knowledge,and an image-driven regularization which is learned by some training *** model can be solved by classical ε-constraint *** results show that:the experimental effectiveness of each term in the regularization accords with the corresponding theoretical proof;the proposed method outperforms other PDE-based methods on image denoising and deblurring.

关键词： Learning idea TV-based model constraint ε-constraint method image restoration

来源：评论

学校读者我要写书评

暂无评论

Reliability-based model for generation and transmission expansion planning

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第2期11卷 504-511页

作者： Ahmadi, Abdollah Mavalizadeh, Hani Zobaa, Ahmed F. Shayanfar, Heidar Ali Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW Australia Iran Univ Sci & Technol Sch Elect Engn Ctr Excellence Power Syst Automat & Operat Tehran Iran Brunel Univ London Coll Engn Design & Phys Sci Uxbridge Middx England

This study presents a mixed integer linear multi-objective model based on information gap decision theory, which is used to solve coordinated multiyear generation and transmission expansion planning problems. The model maximises the robustness of each uncertain parameter while a maximum allowable budget range is set. Fuel transportation price is considered. The results provide a numerical tool for system planner to help him adjust the appropriate level of robustness for each uncertain parameter of the problem. Extra limits on security, gaseous emission and fuel availability are considered. A multi-objective method called the.-constraint method is used here to maximise the robust region of load and investment costs simultaneously. The model is implemented on a six-bus Garver test system and 24-bus IEEE test system. The numerical results show the good performance of the model.

关键词： power transmission planning power transmission reliability integer programming linear programming decision theory power generation planning power generation reliability reliability-based model transmission expansion planning mixed integer linear multiobjective model information gap decision theory coordinated multiyear generation fuel transportation price gaseous emission fuel availability multiobjective method ε-constraint method investment costs six-bus Garver test system 24-bus IEEE test system

来源：评论

学校读者我要写书评

暂无评论

Solving a bi-objective mathematical model for location-routing problem with time windows in multi-echelon reverse logistics using metaheuristic procedure

引用

Journal of Industrial Engineering International 2016年第4期12卷 469-483页

作者： Ghezavati, V.R. Beigi, M. School of Industrial Engineering Islamic Azad University South Tehran Branch Tehran Iran

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among established facilities and existing demand points. In this paper, the location-routing problem with time window (LRPTW) and homogeneous fleet type and designing a multi-echelon, and capacitated reverse logistics network, are considered which may arise in many real-life situations in logistics management. Our proposed RL network consists of hybrid collection/inspection centers, recovery centers and disposal centers. Here, we present a new bi-objective mathematical programming (BOMP) for LRPTW in reverse logistic. Since this type of problem is NP-hard, the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to obtain the Pareto frontier for the given problem. Several numerical examples are presented to illustrate the effectiveness of the proposed model and algorithm. Also, the present work is an effort to effectively implement the ε-constraint method in GAMS software for producing the Pareto-optimal solutions in a BOMP. The results of the proposed algorithm have been compared with the ε-constraint method. The computational results show that the ε-constraint method is able to solve small-size instances to optimality within reasonable computing times, and for medium-to-large-sized problems, the proposed NSGA-II works better than the ε-constraint. © 2016, The Author(s).

关键词： Bi-objective model Location-routing problem NSGA-II Reverse logistics network Time window ε-constraint method

来源：评论

学校读者我要写书评

暂无评论

A New Bi-objective Location-routing Problem for Distribution of Perishable Products: Evolutionary Computation Approach

引用

Journal of Mathematical Modelling and Algorithms in Operations Research 2015年第3期14卷 287-312页

作者： Khalili-Damghani, Kaveh Abtahi, Amir-Reza Ghasemi, Amir Department of Industrial Engineering South-Tehran Branch Islamic Azad University Tehran Iran Department of Knowledge Engineering and Decision Sciences Faculty of Management Economics University of Economic Sciences Tehran Iran

Supply, manufacture, and distribution of perishable products are challenging jobs in supply chains. Location of warehouses and routing of vehicles are essential issues to distribute perishable products properly. In this paper, a new bi-objective mixed integer mathematical programming is proposed to reduce the total cost of the supply chain and to balance the workload of distribution centers while the due dates of delivery of perishable product are met, concurrently. The considered properties and constraints of proposed model made it well-posed to illustrate the real life situation. As the proposed model is NP-Hard, an evolutionary algorithm called Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is customized to solve the problem. The structure of chromosome and genetic operators are customized for the problem. The performance of proposed NSGA-II and an efficient exact Multi-objective method, called ε-constraint, is compared using accuracy and diversity metrics on several benchmark instances. © 2015, Springer Science+Business Media Dordrecht.

关键词： Bi-objective optimization Distribution of perishable products Location-routing problem Mixed-integer programming Multi-objective genetic algorithm ε-constraint method

来源：评论

学校读者我要写书评

暂无评论

Multi-criteria Batch Scheduling under Time-of-Use Tariffs

Multi-criteria Batch Scheduling under Time-of-Use Tariffs

引用

作者： Junheng Cheng Universite Paris-Saclay

学位级别：博士

The industrial sector is the largest consumer of the world's total energy and most of its consumption form is electricity. To strengthen the grid's peak load regulation ability, time-of-use (TOU) electricity pricing policy has been implemented in many countries to encourage electricity users to shift their consumption from on-peak periods to off-peak periods. This strategy provides a good opportunity for manufacturers to reduce their energy bills, especially for energy-intensive ones, where batch scheduling is often involved. In this thesis, several bi-objective batch scheduling prob- lems under TOU tariffs are studied. We first investigate a single machine batch scheduling problem under TOU tariffs with the objectives of mini- mizing total electricity cost and makespan. This primary work is extended by further considering machine on/off switching. Finally, a parallel batch machines scheduling problem under TOU tariffs with non-identical job sizes to minimize total electricity cost and number of enabled machines is studied. For each of the considered problems, appropriate mathematical models are established, their complexities are demonstrated. Different bi- objective resolution methods are developed, including knapsack heuristic based ε-constraint method, multiple knapsack heuristic based ε-constraint method, bin packing heuristic based ε-constraint method and two-stage heuristic based iterative search algorithm. The performance of the pro- posed methods is evaluated by randomly generated instances. Extensive numerical results show that the proposed algorithms are more efficient and/or effective for the studied problems than the commercial software CPLEX.

关键词： Bi-objective optimization Batch scheduling Time-of-use electricity tariffs Mathematical programming ε-constraint method Heuristics

来源：评论

学校读者我要写书评

暂无评论

SHELTER SITE LOCATION UNDER DEMAND UNCERTAINTY: A CHANCE-CONSTRAINED MULTI-OBJECTIVE MODELING FRAMEWORK

SHELTER SITE LOCATION UNDER DEMAND UNCERTAINTY: A CHANCE-CON...

引用

作者： Omer Burak Kinay Bilkent University

学位级别：硕士

Shelters have a very critical role in disaster relief since they provide accommo- dation and necessary services for the disaster victims who lost their homes. The selection of their locations among many candidate points is a task that should be carried out with a proper methodology that generates applicable and fairness- based plans. Since this selection process is done before the occurrence of disas- ters, it is important to take demand variability into account. Motivated by this, the problem of determining shelter site locations under demand uncertainty is addressed. In particular, a chance-constrained mathematical model that takes demand as a stochastic input is developed. By using a linearization approach that utilizes special ordered set of type 2 (SOS2) variables, a mixed-integer linear programming model is formulated. Using the proposed formulation, instances of the problem using data associated with Istanbul are solved. The results in- dicate that capturing uncertainty in the shelter site location problem by means of chance constraints may lead to solutions that are much different from those obtained from a deterministic setting. During these computational analysis, it is observed that the single-objective model is prone to generate many alternative so- lutions with different characteristics of important quality measures. Motivated by this, a multi-objective framework is developed for this problem in order to have a stronger modeling approach that generates only non-dominated solutions for the selected performance measures. The ε-constraint method is used for scalar- ization of the model. Bi-objective and 3-objective algorithms are presented for detecting all the efficient solutions of a given setting. Unlike the single-objective configuration, the decision makers could be supplied with much richer informa- tion by reporting many non-dominated solutions and allowing them to evaluate the trade-offs based on their preferences.

关键词： Disaster Management Shelter Site Location Discrete Facility Location Stochastic Programming Chance-constraints Multiple-Objective Programming ε-constraint method

来源：评论

学校读者我要写书评

暂无评论

The impact of lead time variability on the total cost of a supply chain network

The impact of lead time variability on the total cost of a s...

引用

作者： Tyrone Dorlandt Vrije Universiteit Amsterdam

学位级别：硕士

Purpose: investigating the effect of lead time variability on the total cost of a supply chain network to gain more knowledge about the impact lead time variability has. Design/methodology/approach: A mixed integer linear program model has been developed to calculate Pareto efficient outcomes for different groups of lead time variability among different datasets. The Pareto frontiers between the objectives of minimizing cost and minimizing lead time are constructed using the ε-constraint method. These Pareto solution sets are compared and analysed. Furthermore an significance test has been executed to review the difference of average cost between lead time variability groups. Findings: a high change of Pareto improving solutions under the Pareto efficient solution sets, but no significant difference on average total cost between the benchmark and lead time variability groups. Research limitations/implications: Two research limitations were present in this thesis: The construction of the lead time could be enhanced and the approach on lead time and other parameters could be stochastic instead of deterministic. Practical implications: Two important insight regarding lead time variability are obtained. First lead time variability has a noteworthy impact when considering the Pareto efficient outcomes. Different groups can have vastly different outcomes. Second, there is no significant difference in the average total cost between the use of lead time variability and no lead time variability. Social implications: none. Originality/value: There is a large absence of the use of lead time variability in current supply chain network research. Most of the articles ignore the existence of lead time variability and neglect to mention the reason for not including variability into their research. It is therefore important to gain knowledge on the implication lead time variability has.

关键词： Mixed integer linear program lead time variability supply chain network ε-constraint method

来源：评论

学校读者我要写书评

暂无评论

An innovative technique for optimization and sensitivity analysis of a PV/DG/BESS based on converged Henry gas solubility optimizer: A case study

引用

IET Generation, Transmission & Distribution 2023年第21期17卷 4735-4749页

作者： Noradin Ghadimi Majid Sedaghat Keyvan Karamnejadi Azar Behdad Arandian Gholamreza Fathi Mojtaba Ghadamyari Young Researchers and Elite Club Ardabil Branch Islamic Azad University Ardabil Iran Faculty of Electrical Engineering Shahid Beheshti University Tehran Iran Department of Electrical Engineering Urmia branch Islamic Azad University Urmia Iran Department of Electrical Engineering Dolatabad Branch Islamic Azad University Isfahan Iran Department of Electrical Engineering Power & Water University of Technology (PWUT) Tehran Iran Department of Electrical Engineering Shahid Beheshti University Tehran Iran

The construction of hybrid power plants with renewable resources can bring significant economic benefits if it is evaluated economically and technically. The present study uses a novel optimum methodology for designing a combined solar/battery/diesel system in Yarkant, Xinjiang Uyghur Autonomous Region of China. In the desired system, the green energy combined system is designed to reduce the use of diesel generators. The diesel generator has been used in the photovoltaic, diesel, and battery to support green energy resources and batteries, as well as function as a backup generator for critical times whenever the production of green energy resources is low or the load demand is high. The amount of CO2 emitted, the probability of load shortage and the system cost on yearly basis are the major goals in the process of optimization. Here, the single-objective problem is created by using the ε-constraint technique to combine the many objectives. An improved Henry gas solubility optimizer handles the problem of optimization. To demonstrate the superiority of the strategy, a comparison is conducted between the simulation outcomes of the offered system, HOMER, and particle swarm optimizer -based optimum systems from the literature. The sensitivity of each parameter is also examined using sensitivity analysis.

关键词： converged Henry gas solubility optimization algorithm hybrid renewable energy system multi-objective optimization sensitivity analysis Taklamakan desert ε-constraint method

来源：评论

学校读者我要写书评

暂无评论

A bi-objective model for nursing home location and allocation problem

A bi-objective model for nursing home location and allocatio...

引用

International Conference on Services Systems and Services Management, ICSSSM

作者： Shijin Wang Shuan Ma Bin Li Xue Li School of Economics and Management Tongji University Shanghai P.R. China College of Architecture and Urban Planning Tongji University Shanghai P.R. China

ISBN: (纸本)9781509028436

In recent years, along with the more and more serious pension issues, nursing home construction becomes an important project. Meanwhile, it is crucial for decision makers to determine the location of a nursing home before its construction. An effective location planning could achieve reasonable resources allocation and social fairness. This paper considers a nursing home location and allocation problem with two objectives. The first objective is to minimize the total construction costs, which is considered from the perspective of the government. For the elderly people, their expectations are their allocated nursing homes close enough to their children's communities. Therefore, the second objective is to minimize the total distances. A bi-objective mixed-integer programming(MIP) model is formulated and an exact ε-constraint method is adopted to obtain a set of optimal Pareto solutions. A case study is conducted with comparisons. The obtained results demonstrate the proposed model and adopted method are suitable for the real-world nursing home location and allocation problem.

关键词： Nursing home Facility location Resource allocation ε-constraint method Pareto solution

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：