检索结果-内蒙古大学图书馆

Optimal economic dispatch of FC-CHP based heat and power micro-grids

APPLIED THERMAL ENGINEERING 2017年 114卷 756-769页

作者： Nazari-Heris, Morteza Abapour, Saeed Mohammadi-Ivatloo, Behnam Univ Tabriz Fac Elect & Comp Engn Smart Energy Syst Lab Tabriz Iran

Micro-grids (MGs) are introduced as a solution for distributed energy resource (DER) units and energy storage systems (ESSs) to participate in providing the required electricity demand of controllable and non-controllable loads. In this paper, the authors study the short-term scheduling of grid-connected industrial heat and power MG which contains a fuel cell (FC) unit, combined heat and power (CHP) generation units, power-only unit, boiler, battery storage system, and heat buffer tank. The paper is aimed to solve the multi-objective MG dispatch problem containing cost and emission minimization with the considerations of demand response program and uncertainties. A probabilistic framework based on a scenario method, which is considered for load demand and price signals, is employed to overcome the uncertainties in the optimal energy management of the MG. In order to reduce operational cost, time of -use rates of demand response programs have been modeled, and the effects of such programs on the load profile have been discussed. To solve the multi-objective optimization problem, the epsilon-constraint method is used and a fuzzy satisfying approach has been employed to select the best compromise solution. Three cases are studied in this research to confirm the performanC'e of the proposed method: islanded mode, grid-connected mode, and the impact of time of the use-demand response program on MG scheduling. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Fuel cell Combined heat and power (CHP) Economic dispatch Demand response (DR) program Heat and power micro-grid (MG) Storage devices epsilon-constraint method

来源：评论

学校读者我要写书评

暂无评论

An integrated multi-objective framework for solving multi-period project selection problems

引用

APPLIED MATHEMATICS AND COMPUTATION 2012年第6期219卷 3122-3138页

作者： Khalili-Damghani, Kaveh Tavana, Madjid Sadi-Nezhad, Soheil Islamic Azad Univ S Tehran Branch Dept Ind Engn Tehran Iran La Salle Univ Lindback Distinguished Chair Informat Syst & Deci Philadelphia PA 19141 USA

Investment managers are multi-objective decision-makers (DMs) who make portfolio decisions by maximizing profits and minimizing risks over a multi-period planning horizon. Portfolio decisions are complex multi-objective problems which include both tangible and intangible factors. We propose an integrated multi-objective framework for project portfolio selection with respect to both the profits and risks objectives. The proposed method is based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and an efficient version of the epsilon-constraint method. TOPSIS is used to reduce the Multi-Objective Decision Making (MODM) problem into a bi-objective problem. The efficient epsilon-constraint method is used to generate non-dominated solutions with a pre-defined and arbitrary resolution on the Pareto front of the aforementioned bi-objective problem. The results from the integrated framework proposed in this study are compared with the results from the conventional epsilon-constraint method based on a series of simulated benchmark cases. A sensitivity analysis is performed to study the sensitivity of the relative importance weights of the objective functions in re-generating the Pareto front. The practical application of the proposed framework illustrates the efficacy of the procedures and algorithms. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Multi-objective decision making epsilon-constraint method Pareto front TOPSIS Mathematical programming Multi-period project selection

来源：评论

学校读者我要写书评

暂无评论

Optimization, validation and analyses of a hybrid PV-battery-diesel power system using enhanced electromagnetic field optimization algorithm and ε-constraint

引用

ENERGY REPORTS 2024年 11卷 5335-5349页

作者： Zhu, Chaoyang Zhang, Yunxiang Wang, Mengxia Deng, Jinxin Cai, Yiwei Wei, Wei Guo, Mengxing Univ China Inst Social Innovat & Publ Culture Commun Beijing 100000 Peoples R China Int Inst Engn Psychol Denver CO 80201 USA Univ Illinois Champaign Urbana Champaign IL 61801 USA Hainan Vocat Univ Sci & Technol Haikou 570100 Hainan Peoples R China Shenzhen High level Talents Dev Promot Assoc Shenzhen 518000 Guangdong Peoples R China CDA Int Accelerator Shenzhen 518000 Guangdong Peoples R China Shenzhen Res Inst Beijing Inst Technol Shenzhen 518000 Guangdong Peoples R China Univ Wollongong Wollongong NSW 2522 Australia Xian Univ Technol Sch Comp Sci & Engn Xian 710048 Shaanxi Peoples R China Shandong Open Univ Jinan 250000 Shandong Peoples R China

This study introduces and assesses a hybrid renewable energy system tailored for a practical, off-grid location. The integrated power system comprises a diesel generator, photovoltaic panels, battery storage system, and a converter. The primary objective is to formulate a system exhibiting optimal performance concerning cost, carbon emissions, and load satisfaction, necessitating a three-objective optimization approach. Leveraging the epsilon-constraint method alongside an enhanced optimization algorithm, the study compares the enhanced algorithm against its original version and established optimization algorithms using intricate benchmark functions. Outcomes indicate the enhanced algorithm's superiority, manifested through minimal error and standard deviation. Subsequently, the enhanced hybrid optimization method is employed to optimize the design and operation of the proposed power system, considering economic, environmental, and technical facets. Rigorous sensitivity analyses ascertain the system cost's responsiveness to varying parameters. To validate the efficacy of the proposed optimization approach, a parallel optimization of the hybrid power system is conducted using HOMER software. Results demonstrate that the proposed hybrid optimization method not only meets defined limits but also minimizes carbon emissions, emphasizing its effectiveness in designing sustainable and efficient off-grid energy systems.

关键词： Multi-objective optimization Enhanced electromagnetic field optimization algorithm epsilon-constraint method Hybrid renewable energy system Photovoltaic

来源：评论

学校读者我要写书评

暂无评论

Efficient methods for a bi-objective nursing home location and allocation problem: A case study

引用

APPLIED SOFT COMPUTING 2018年 65卷 280-291页

作者： Wang, Shijin Ma, Shuan Tongji Univ Sch Econ & Management Shanghai Peoples R China

In recent years, due to 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 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 weighted distances. To obtain exact solutions within reasonable computation time, valid equalities are proposed to enhance exact epsilon-constraint method. For large-scale problems, a non-dominated sorting genetic algorithm (NSGA-II) is applied, in which a new chromosome representation is used and a heuristic method is designed for the allocation subproblem. A multi-objective simulated annealing (MOSA) algorithm is also adapted to the problem. Finally, a case study with two data sets is conducted and computational comparisons are made with both exact methods and the algorithms. The results show the promising performance of the proposed enhanced epsilon-constraint method and the modified NSGA-II. (c) 2018 Elsevier B.V. All rights reserved.

关键词： Nursing home Facility location and allocation Bi-objective optimization epsilon-constraint method NSGA-II MOSA

来源：评论

学校读者我要写书评

暂无评论

Multi-objective models for biomass supply chain planning with economic and carbon footprint consideration

引用

ENERGY REPORTS 2021年 7卷 6833-6843页

作者： Duc, Duy Nguyen Meejaroen, Pasakorn Nananukul, Narameth Thammasat Univ Sch Management Technol Sirindhorn Int Inst Technol Bangkok Thailand

This paper focuses on designing multi-objective biomass supply chain planning models that aim to simultaneously minimize the total cost and the carbon footprint from the transportation. Stochastic and fuzzy models were developed for making strategic (optimal plant locations) and tactical decisions (material flows, truck types, etc.), while capturing the uncertainty of the demand. An epsilon-constraint method was applied to generate optimal solutions from these models. Managerial insights are provided based on a practical case study at a biomass plant in the Lower Northern region of Thailand;nine biomass plant candidates, nine rice husks suppliers and eight trucks were considered in the case study. A sensitivity analysis has been conducted to compare the results from the two models. The stochastic model can take into account all the scenarios of demand, while the fuzzy model can handle only a certain level of demand defined by a centroid value. The stochastic model needs to take into account a large number of variables and constraints, and therefore, requires more runtime to define an optimal solution, as compared to the fuzzy model. The trade-off between the operating cost and carbon emissions from both the models are provided with managerial insights. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Biomass supply chain management epsilon-constraint method Multi-objective model Fuzzy model Stochastic model Carbon footprint Renewable energy

来源：评论

学校读者我要写书评

暂无评论

New criteria for configuration of cellular manufacturing considering product mix variation

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2016年第0期98卷 413-426页

作者： Bootaki, Behrang Mandavi, Iraj Paydar, Mohammad Mandi Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Babol Univ Technol Dept Ind Engn Babol Sar Iran

This paper deals with configuring manufacturing cells when product mix variation occurs. Most of researches have addressed the cell formation problem when part-machine incidence matrix is constant even for dynamic/stochastic case. But to the nature of CMS in manufacturing products in mid-variety and mid-volume, the product mix variation is not too far-fetched. Product mix variation causes the part machine incidence matrix to change. To formulate the proposed problem two different criteria are considered which one relates to worker experts and another to worker relations. The first object considers the maximizing the expert levels in manufacturing cells. While the second object tries to maximize the interest levels in manufacturing cells. To make these concepts practical, a mathematical formulation which minimizes the voids of both worker-machine and worker-worker incidence matrices is developed. Due to the non-homogenous nature of the objective functions and possible conflicts, a bi-objective programming approach is applied. To find the Pareto-optimal front, the augmented epsilon-constraint method (AUGMECON) is applied. Since AUGMECON may not provide non-dominated set in a reasonable time, especially for large-size instances, NSGAII algorithm is customized and applied to produce optimal/near optimal Pareto solutions. To assess the performance of the proposed NSGAII algorithm, several randomly generated test problems were solved for a set of well-known multi-objective performance metrics. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Cellular manufacturing systems Product mix variation Worker interest epsilon-constraint method NSGAII

来源：评论

学校读者我要写书评

暂无评论

An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production

引用

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2020年第8期58卷 2283-2314页

作者： Wang, Shijin Wang, Xiaodong Chu, Feng Yu, Jianbo Tongji Univ Sch Econ & Management Shanghai Peoples R China Univ Paris Saclay Univ Evry IBISC Paris France Fuzhou Univ Sch Econ & Management Fuzhou Fujian Peoples R China Tongji Univ Sch Mech Engn Shanghai Peoples R China

Energy-efficient scheduling is highly necessary for energy-intensive industries, such as glass, mould or chemical production. Inspired by a real-world glass-ceramics production process, this paper investigates a bi-criteria energy-efficient two-stage hybrid flow shop scheduling problem, in which parallel machines with eligibility are at stage 1 and a batch machine is at stage 2. The performance measures considered are makespan and total energy consumption. Time-of-use (TOU) electricity prices and different states of machines (working, idle and turnoff) are integrated. To tackle this problem, a mixed integer programming (MIP) is formulated, based on which an augmented epsilon-constraint (AUGMECON) method is adopted to obtain the exact Pareto front. A problem-tailored constructive heuristic method with local search strategy, a bi-objective tabu search algorithm and a bi-objective ant colony optimisation algorithm are developed to deal with medium- and large-scale problems. Extensive computational experiments are conducted, and a real-world case is solved. The results show effectiveness of the proposed methods, in particular the bi-objective tabu search.

关键词： two-stage hybrid flow shop total energy consumption epsilon-constraint method constructive heuristic bi-objective tabu search bi-objective ant colony optimisation

来源：评论

学校读者我要写书评

暂无评论

Multi-objective mathematical modeling for sustainable supply chain management in the paper industry

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2019年 135卷 1092-1102页

作者： Vafaeenezhad, Taha Tavakkoli-Moghaddam, Reza Cheikhrouhou, Naoufel Univ Tehran Sch Ind Engn Coll Engn Tehran Iran Lorraine Univ LGIPM Metz France Arts & Metiers ParisTech LCFC Metz France Univ Appl Sci Western Switzerland Geneva Sch Business Adm HES SO Geneva Switzerland

This work develops a multi-objective linear programming model for a multi-echelon, multi-product, multi-period supply chain planning. This model considers all dimensions of sustainable development paradigm simultaneously and expands six objective functions for making the model realistic. To solve this model and large-scale sustainable supply chain management, an improved version of the augmented epsilon-constraint method (AUGME-CON2) is used. Computational results illustrate the proposed model admitted various progresses in all the three pillars of sustainable development;namely remarkable progress, mildly progress and irregular one, respectively. In addition, important managerial insights are provided. Trade-off interactions between multi-objectives are perceived by the obtained Pareto solutions that represents the cost of being sustainable from the point of optimizing the social factors and environmental impacts. An application to the paper industry is presented and discussed.

关键词： Supply chain management Multi-objective programming model Chemical process Sustainability epsilon-constraint method

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Probabilistic Fractional Programming Problem Involving Two Parameters Cauchy Distribution

引用

MATHEMATICAL MODELLING AND ANALYSIS 2019年第3期24卷 385-403页

作者： Acharya, Srikumar Belay, Berhanu Mishra, Rajashree KIIT Deemed Be Univ Sch Appl Sci Dept Math Bhubaneswar 751024 India

The paper presents the solution methodology of a multi-objective probabilistic fractional programming problem, where the parameters of the right hand side constraints follow Cauchy distribution. The proposed mathematical model can not be solved directly. The solution procedure is completed in three steps. In first step, multi-objective probabilistic fractional programming problem is converted to deterministic multi-objective fractional mathematical programming problem. In the second step, it is converted to its equivalent multi-objective mathematical programming problem. Finally, epsilon-constraint method is applied to find the best compromise solution. A numerical example and application are presented to demonstrate the procedure of proposed mathematical model.

关键词： multi-objective programming problem probabilistic programming problem fractional programming problem epsilon-constraint method

来源：评论

学校读者我要写书评

暂无评论

Multi-objective multi-mode resource constrained project scheduling problem using Pareto-based algorithms

引用

COMPUTING 2019年第6期101卷 547-570页

作者： Tirkolaee, Erfan Babaee Goli, Alireza Hematian, Milad Sangaiah, Arun Kumar Han, Tao Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Islamic Azad Univ Ayatollah Amoli Branch Young Researchers & Elite Club Amol Iran Yazd Univ Dept Ind Engn Yazd Iran Vellore Inst Technol Sch Comp Sci & Engn Vellore 632014 Tamil Nadu India Dongguan Univ Technol DGUT CNAM Inst Dongguan Guangdong Peoples R China

This study addresses the multi-objective multi-mode resource-constrained project scheduling problem with payment planning where the activities can be done through one of the possible modes and the objectives are to maximize the net present value and minimize the completion time concurrently. Moreover, renewable resources including manpower, machinery, and equipment as well as non-renewable ones such as consumable resources and budget are considered to make the model closer to the real-world. To this end, a non-linear programming model is proposed to formulate the problem based on the suggested assumptions. To validate the model, several random instances are designed and solved by GAMS-BARON solver applying the epsilon-constraint method. For the high NP-hardness of the problem, we develop two metaheuristics of non-dominated sorting genetic algorithm II and multi-objective simulated annealing algorithm to solve the problem. Finally, the performances of the proposed solution techniques are evaluated using some well-known efficient criteria.

关键词： Multi-mode resource-constrained project scheduling problem NPV Payment planning epsilon-constraint method NSGA-II MOSA

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：