检索结果-内蒙古大学图书馆

Study on non-linear planning model of green building energy consumption under multi-objective optimization

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2022年第SUPPL 1期13卷 437-443页

作者： Fan, Miao Su, Danna Bhatt, Mohammed Wasim Mangal, Adarsh Zheng Zhou Railway Vocat & Tech Coll Coll Railway Engn Zhengzhou 450000 Henan Peoples R China Cent Univ Punjab Dept Comp Sci Engn Ghudda India Engn Coll Ajmer Dept Math Ajmer India

The research on economic balance and balanced competition is the initial concept that has reflected the idea of multi-objective programming which is usually encountered in the modeling of green buildings. This concept has laid the base in building a multi-objective optimization problem, for the establishment of model and calculation. By establishing a nonlinear planning model for determining the control target value of the project and by calculating the results, it is assumed that the sample is estimated as a very large likelihood, with consistency and non-biasing. In this paper several variables are analyzed and focus has been paid to weather conditions by making several interpretations: If the weather is good, the p(it) = 1, the engine can successfully complete the project amount of the plan;if constructed, when the weather is not conducive to engineering construction, then p(it) < 1 indicates that the increasing amount caused by the imbalance is used. Thus, the imbalance of resources has increased the entire project cost;the usage of closer approach to investment reflects less payment, small use of funds, therefore lower will be the cost. By establishing a model to determine the control target value of the project, the total amount of actual investment is 153.439 million Yuan, after the results calculation is optimized and the total cost after the initial progress plan is 5.34 million Yuan, combined with the project. Using NLP cost optimization is obtained with the overall construction efficiency.

关键词： Nonlinear programming (NLP) Model research Green building energy consumption multi-objective programming

来源：评论

学校读者我要写书评

暂无评论

The role of bank affiliation in bank efficiency: a fuzzy multi-objective data envelopment analysis approach

引用

ANNALS OF OPERATIONS RESEARCH 2022年第2期311卷 611-639页

作者： Boubaker, Sabri Do, Duc Trung Hammami, Helmi Ly, Kim Cuong EM Normandie Business Sch Metis Lab Le Havre France Vietnam Natl Univ Int Sch Hanoi Vietnam Swansea Univ Sch Management Swansea W Glam Wales Rennes Sch Business Rennes France Univ Nottingham Nottingham Univ Business Sch Nottingham England

This paper examines differences in bank efficiency between banks affiliated with single-bank holding companies and those affiliated with multi-bank holding companies by applying a fuzzy multi-objective two-stage data envelopment analysis technique. Using a sample of U.S. commercial banks covering 1994-2018, the results show that banks affiliated with multi-bank holding companies are more efficient than those affiliated with single-bank holding companies, suggesting that the former takes advantage of their parents' resources to enhance their efficiency, consistent with the internal capital market theory. They also show that banks with a powerful CEO exhibit lower efficiency than others. Moreover, there is an inverted U shape relationship between multi-bank holding company structure and bank efficiency, suggesting the presence of an optimal number of multi-bank holding subsidiaries that maximizes efficiency.

关键词： Bank holding companies Bank efficiency CEO power multi-objective programming Data envelopment analysis

来源：评论

学校读者我要写书评

暂无评论

A multi-objective optimization model for a multi-period mobile facility location problem with environmental and disruption considerations

引用

ANNALS OF OPERATIONS RESEARCH 2022年第2期346卷 1445-1470页

作者： Maliki, Fouad Souier, Mehdi Dahane, Mohammed Ben Abdelaziz, Fouad Mfg Engn Lab Tlemcen MELT Tilimsen Algeria High Sch Appl Sci Tlemcen Tilimsen Algeria High Sch Management Tlemcen Tilimsen Algeria Univ Lorraine LGIPM F-57000 Metz France NEOMA Business Sch Rouen France

The present work addresses a multi-period facility location decision during crisis-Pandemic-situation with highly uncertain demand. Our paper identifies failing distribution centres (DCs) over several periods of time and decides about relocation. Several scenarios arise: DCs can be opened, displaced from one location to another, closed or even reopened during a certain time, using mobile facility. We recommend a multi-objective non-linear mixed-integer mathematical model that identifies, for each period, the best possible location for DCs and their allocation to customers. Our model analyses the trade-off between economic costs and CO2 emissions generated by facilities operations. We suggest a multiobjective approach based on a Non-dominated Sorting Genetic Algorithm II (NSGA-II). Our simulations demonstrate how mobile facility should be managed to ensure a good balance between economic and environmental criteria.

关键词： Facility planning and design multi-objective programming Disruptions Environmental sustainability

来源：评论

学校读者我要写书评

暂无评论

An interactive weighted fuzzy goal programming technique to solve multi-objective reliability optimization problem

引用

Journal of Industrial Engineering International 2019年第1-Sup期15卷 95-104页

作者： Kundu, Tanmay Islam, Sahidul Department of Mathematics University of Kalyani Kalyani 741235 West Bengal India

This paper presents an application of interactive fuzzy goal programming to the nonlinear multi-objective reliability optimization problem considering system reliability and cost of the system as objective functions. As the decision maker always have an intention to produce highly reliable system with minimum cost, therefore, we introduce the interactive method to design a high productivity system here. This method plays an important role to maximize the worst lower bound to obtain the preferred compromise solution which is close to the best upper bound of each objective functions. Until the preferred compromise solution is reached, new lower bounds corresponding to each objective functions will be determined based on the present solution to develop the updated membership functions as well as aspiration levels to resolve the proposed problem. Considering judgmental vagueness of decision maker, here we consider the resources as trapezoidal fuzzy numbers and apply total integral value of fuzzy number to transform into crisp one. To illustrate the methodology and performance of this approach, numerical examples are presented and evaluated by comparing with the other method at the end of this paper. © 2019, The Author(s).

关键词： Fuzzy programming Goal programming Interactive methods multi-objective programming Reliability

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization of crude oil-supply portfolio based on interval prediction data

引用

ANNALS OF OPERATIONS RESEARCH 2022年第2期309卷 611-639页

作者： Sun, Xiaolei Hao, Jun Li, Jianping Chinese Acad Sci Inst Sci & Dev 15 Zhongguancun Beiyitiao Haidian Dist Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Publ Policy & Management 19A Yuquan Rd Beijing 100049 Peoples R China Univ Chinese Acad Sci Sch Econ & Management 80 Zhongguancun East Rd Haidian Dist Beijing 100190 Peoples R China

The optimization of crude oil-supply portfolio is a hot research issue in energy security, which is closely related to the implementation of national strategy and development of economy. Forecasting the demand of crude oil is the basis for portfolio optimization. Therefore, this paper innovatively introduces the decomposition hybrid interval prediction method and proposes a multi-objective programming model in order to provide decision-making support for the formulation of crude oil-supply portfolio scheme. Under the constraints of volume, price and risk, the minimum cost and risk of importing crude oil are achieved. Furthermore, by introducing optimization parameters and risk preference factors, and setting different scenarios for numerical simulation, the results show that (1) decomposition hybrid prediction methods perform better than single prediction methods. (2) As the optimization parameter increases, costs and risks are significantly decreased. Decision-makers can set large parameters to achieve significant optimization of the objective function. (3) The total cost of imported crude oil fluctuates sharply, while the total risk decreases with the increase of risk preference factors under the different scenarios. (4) The fluctuation of price and risk adjustment factors will cause the change of oil-supply portfolio optimization scheme.

关键词： Energy supply security Country risk Decomposition hybrid methodology Interval prediction multi-objective programming

来源：评论

学校读者我要写书评

暂无评论

Integrated Supply Chain Management: A Collaborative System for Fabric Supplier Selection, Order Allocation, and Product Delivery 11

Integrated Supply Chain Management: A Collaborative System f...

引用

11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Gao, Yingao Ding, Xiangqian Li, Song Guo, Baoqi College of Computer Science and Technology Ocean University of China Qingdao China Qingdao Haida Nova Software Consulting Co. Qingdao China

ISBN: (纸本)9798350333664

In today's dynamic and rapidly evolving business landscape, collaborative supply chain management has become a research hotspot in enterprise management. This paper aims to develop a comprehensive supply chain collaboration system by integrating the combination weighting method and multi-objective programming. The critical focus areas encompass fabric supplier selection, order allocation, and product delivery. An evaluation system tailored to the enterprise's characteristics is established for fabric suppliers to achieve this. The comprehensive weighting method is utilized to assign weights to evaluation indicators. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is subsequently used to rank the suppliers. Additionally, considering the unique attributes of the clothing and textile industries, a model is developed for order allocation and product delivery. This model aims to minimize the overall expenses of the supply chain, maximize the weighted value of fabrics considering suppliers' priorities, and meet the order demand from distributors. The applicability and effectiveness of the proposed supply chain collaboration system are validated through actual case studies and the utilization of the Gurobi solver. © 2023 IEEE.

关键词： multi-objective programming supply chain collaboration system TOPSIS

来源：评论

学校读者我要写书评

暂无评论

Optimal Allocation of Water Resources of Beijing-Tianjin-Hebei based on multi-objective programming

引用

2nd International Conference on Energy and Environmental Protection (ICEEP 2013)

作者： Zhang, Chaoliang Fang, Yong Luo, JinChuan Bo, Lin Chinese Acad Sci Acad Math & Syst Sci Beijing Peoples R China

ISBN: (纸本)9783037857427

Water resources are the most valuable natural resources for human's survival and development, and the strategic resources of the national economic and social development. Reasonable utilization and allocation of water resources are the fundamental guarantee for the sustainable development strategy in China. So this paper first forecasts the demand of water for each region, then establishes a multi-objective optimization model of water resources and investigates quantitative methods for the social, economic and environment objectives. According to the specific circumstances of each region, we optimally allocate the water resources in Beijing-Tianjin-Hebei.

关键词： Water Resources Optimal allocation multi-objective programming

来源：评论

学校读者我要写书评

暂无评论

Adapting to climate change in arid agricultural systems: An optimization model for water-energy-food nexus sustainability

引用

AGRICULTURAL WATER MANAGEMENT 2024年 303卷

作者： Radmehr, Riza Brorsen, B. Wade Shayanmehr, Samira Oklahoma State Univ Dept Agr Econ Stillwater OK 74078 USA Ferdowsi Univ Mashhad Dept Agr Econ Mashhad *** Iran

Sustainable management of water, energy, and food (WEF) under climate change will be a significant challenge for arid agricultural systems. This study developed a fractional non-linear multi-objective programming (FNLMOP) model to optimize resource allocation and improve agricultural sustainability in these systems under climate change. The model was designed in the framework of the WEF nexus to simultaneously improved energy productivity (profit/energy), and water productivity (profit/water), while mitigating environmental damage (damage to groundwater resources/output) and ensuring food security in an arid watershed in Iran. The long Ashton research station weather generator (LARS-WG) and the coupled model intercomparison project 6 (CMIP6) were employed to project climate parameters for both future dry and wet conditions. The sustainability of the optimal solutions was then assessed using a hybrid criteria importance through intercriteria correlation (CRITIC)-VIKOR approach. The optimal solutions revealed a reduction in the land under cultivation and produced less water-intensive crops. The optimization model can ensure WEF security, enhancing agricultural system sustainability by optimizing crop cultivation patterns and resource allocation. Current crop choices were highly inefficient with the bigger changes being from the current crops to optimal crops. Climate change showed a substantial but lesser influence on optimal crop choice.

关键词： Crop pattern multi-objective programming Optimal resource allocation Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Water-agriculture-ecology nexus synergetic management based on spatiotemporal equilibrium and water transformation: A case study in Aksu River Basin, China

引用

AGRICULTURAL WATER MANAGEMENT 2024年 303卷

作者： Wang, Taishan Su, Xiaoling Wu, Haijiang Northwest A&F Univ Key Lab Agr Soil & Water Engn Arid & Semiarid Area Minist Educ Yangling 712100 Peoples R China Northwest A&F Univ Coll Water Resources & Architectural Engn Yangling 712100 Shaanxi Peoples R China

The temporal variability and spatial heterogeneity characteristics of the water-agriculture-ecology (WAE) nexus system have aggravated the difficulties in its synergetic management. Besides, in the inland river basin, the surface water and groundwater are tightly linked by the combination of canal and well irrigation. To address these issues, a spatiotemporal equilibrium-water transformation based water-agriculture-ecology nexus synergetic management (SEWT-WAE) model was proposed by incorporating a spatio-temporal robust optimization method and linear water transformation model. The SEWT-WAE model was then applied to the Aksu River Basin, an inland river basin of Xinjiang, China. The results indicated that the SEWT-WAE model was highly effective in achieving spatiotemporal equilibrium in groundwater balance and ecological water utilization, as well as in the integrated management of surface water and groundwater across upstream and downstream regions. The optimal synergetic management scheme was obtained based on the coordinated development degree. Compared to the current situation: (i) the irrigation amount provided by the surface water (groundwater) in the Tabei (Tanan) irrigation district was increased (decreased) by 21.4 % (70.2 %);(ii) the irrigated areas of grain crops and gardens were increased by 30.4 % and 20.1 %, respectively, while the irrigated area of cotton was decreased by 19.4 %;(iii) the ecological water utilization of the Populus euphratica forest was increased by 17.81 %. Overall, this study presents a new optimization model for achieving spatiotemporal equilibrium and conjunctive use of surface water and groundwater and provides decision support for WAE nexus synergetic management in the inland river basin.

关键词： multi-objective programming Robust optimization Conjunctive use multiple criteria analysis Water resource management Irrigation water

来源：评论

学校读者我要写书评

暂无评论

Particle Swarm Optimization-Based multi-objective Planning Model for Marketing Strategy Decision

引用

JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2024年第16期33卷

作者： Li, Bohan Guo, Qi Univ Illinois Dept Biostat Chicago IL 60607 USA Univ Illinois Dept Business Adm Champaign IL 61820 USA

Intelligent algorithms have shown promise in supporting marketing strategy decisions through data mining. However, existing methods have primarily relied on expertise, lacking autonomous decision-making abilities. Consequently, a marketing strategy decision model based on particle swarm optimization and multi-objective programming is proposed. This study first explores the potential for integrating particle optimization and multi-objective programming models partially, and then assesses the overall effectiveness of each marketing strategy by defining a fitness function. Subsequently, the particle swarm optimization algorithm is employed to search for and optimize decision variables to identify the optimal combination of marketing strategies. Finally, several simulation experiments are conducted using external real data. The research findings indicate that the algorithm's error rate in this study was initially 0.23. However, after 500 training sessions, it decreased to 0.08 and maintained a relatively low level. The proportion of marketing strategy revenue increased by 15.2 percentage points between 0 and 100 training sessions, then remained relatively stable at over 30%. Its revenue proportion continued to rise during the training process, significantly surpassing that of other algorithms.

关键词： Particle swarm optimization multi-objective programming decision-making algorithm optimization

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：