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A genetic algorithm for solving bus terminal location problem using data envelopment analysis with multi-objective programming

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ANNALS OF OPERATIONS RESEARCH 2022年第1期309卷 259-276页

作者： Taghavi, Atefeh Ghanbari, Reza Ghorbani-Moghadam, Khatere Davoodi, Alireza Emrouznejad, Ali Ferdowsi Univ Mashhad Fac Math Sci Dept Appl Math Mashhad Razavi Khorasan Iran Ferdowsi Univ Mashhad Fac Math Sci Dept Appl Math Optimizat Lab Mashhad Razavi Khorasan Iran Islamic Azad Univ Dept Math Neyshabur Branch Neyshabur Iran Aston Univ Aston Business Sch Birmingham W Midlands England

Due to the urban expansion and population increasing, bus network design is an important problem in the public transportation. Functional aspect of bus networks such as the fuel consumption and depreciation of buses and also spatial aspects of bus networks such as station and terminal locations or access rate to the buses are not proper conditions in most cities. Therefore, having an efficient method to evaluate the performance of bus lines by considering both functional and spatial aspects is essential. In this paper, we propose a new model for the bus terminal location problem using data envelopment analysis with multi-objective programming approach. In this model, we want to find efficient allocation patterns for assigning stations terminals, and also we investigate the optimal locations for deploying terminals. Hence, we use a genetic algorithm for solving our model. By using the simultaneous combination of data envelopment analysis and bus terminal location problem, two types of efficiencies are optimized: Spatial efficiency as measured by finding allocation patterns with the most serving amount and the terminals' efficiency in serving demands as measured by the data envelopment analysis efficiency score for selected allocation patterns. This approach is useful when terminals' efficiency is one of the important criteria in choosing the optimal terminals location for decision-makers.

关键词： Bus terminal location problem Data envelopment analysis Efficiency Genetic algorithm multi objective programming

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Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option

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ENERGY 2017年 118卷 827-839页

作者： Tabar, Vahid Sohrabi Jirdehi, Mehdi Ahmadi Hemmati, Reza Kermanshah Univ Technol Dept Elect Engn Kermanshah Iran

Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing., Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Augmented Epsilon-constraint method Microgrid multi objective programming Portable renewable energy resource Stochastic programming

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Water quality constrained adjustment planning for regional breeding management with nonlinear programming model under uncertainty in Wenchang City, China

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HELIYON 2024年第16期10卷 e35347页

作者： Wang, Shen Xie, Xuesong Wu, Jing Wang, Siyi Lv, Lianhong Chinese Res Inst Environm Sci Beijing 100012 Peoples R China

Basin water pollution caused by livestock, poultry and fish breeding is still a serious problem for remote villages, however, reliable regional breeding management programming have the potentials to improve pollution status. This paper focuses on the optimal model design and water quality analysis of the livestock, poultry and fish breeding system for Wenchang City, China. Methods of multi-objective programming (MOP), interval parameter programming (IPP), fuzzystochastic parameter programming (FSPP), and chance constrained programming (CCP) were incorporated into the developed model to tackle multi uncertainties described by interval values, probability distributions, fuzzy membership function. Based on the estimation of local breeding potential and current situation of surface water section, a multi-objective mixed fuzzy-stochastic nonlinear programming optimization model is presented with one-dimensional water quality model. In order to evaluate the environmental carrying capacity of livestock, poultry and fishery manure, predict its development trend and investigate the implementation effect of different emission reduction policies, this paper designs quantization system of the urban water environmental carrying capacity for the model. The results indicated that the water environment pollutant absorption capacity and carrying capacity of Wenchang city have approached the limit especially the towns in the northeast of City which limited the overall development space of the City. The modeling results are valuable for supporting the adjustment of the existing livestock, poultry and fish breeding schemes within a complicated system benefit and surface water quality situation under uncertainty.

关键词： Livestock Poultry and fish breeding Surface water quality multi objective programming One-dimensional water quality model multi-uncertainty

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Hierarchical Coverage Location Model of Urban Power Emergency Service Point

Hierarchical Coverage Location Model of Urban Power Emergenc...

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IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

作者： Hu, Tianmu Hu, Xiaodong Feng, Shuming Jiangsu Elect Power Informat Technol Co Ltd ERP Business Dept Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781450391870

For the location of emergency material storage in emergency service of power field, most of the existing studies are based on general logistics, do not select the location according to the actual situation of the region, and do not take into account time constraints, costs, coverage and other factors. There are also loopholes in the construction of emergency system. Therefore, this article analyzes the urban power emergency service points by the classification of demand points, establishes a multi-objective hierarchical coverage model with the maximum coverage and the minimum total loss, and introduces the traffic weighting coefficient into the model. Finally, the immune algorithm is used to verify the optimized multi objective programming hierarchical coverage model. The experiments show that the proposed method can provide services for emergency demand points in time and efficiently.

关键词： Emergency Location Hierarchical Coverage Immune Algorithm multi objective programming

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A multi-objective optimization model for dissolving circular shareholdings in Korean conglomerates

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SOCIO-ECONOMIC PLANNING SCIENCES 2022年 82卷

作者： Jung, Jihye Choi, In-Chan Korea Univ Sch Ind Management Engn Syst Optimizat Lab 145 Anam Ro Seoul South Korea

Circular shareholding is an intriguing ownership structure that enables a major shareholder to gain control of subsidiaries with only small investments. The conflict between the public interest and corporate interest regarding circular shareholding has presented policymakers with unresolved legal issues. To support systematic decision making by policymakers in this circumstance, we propose a multi-objective bilinear optimization model to address the circular shareholding problem. The proposed model provides policymakers with various scenarios corporates could make, assuming the enforcement of regulatory law on circular shareholding along with consideration of the public interest with different weights. We also conduct computational analysis on the model with real data from conglomerates in Korea, where debates about circular shareholding are ongoing. The results show clear patterns between obtained solutions, suggesting the possibility of a quantitative basis for legislation regarding circular shareholding and corporate governance.

关键词： multi objective programming Circular shareholding Mixed-integer optimization model Korean conglomerate

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Maximising the circular economy and sustainability outcomes: An end-of-life tyre recycling outlets selection model

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2021年 232卷

作者： Lee, Sir Yee Hu, Jiayao Lim, Ming K. Coventry Univ Ctr Business Soc Jaguar BldgPriory St Coventry W Midlands England Newcastle Univ Business Sch Barrack Rd Newcastle Upon Tyne Tyne & Wear England

The increasing concern for sustainability and longing for the transition into the circular economy has fostered an immense interest in re-configuring the end-of-life tyre supply networks. However, the existing literature is incapable of providing sufficient guidance in regard to the allocation of end-of-life tyre among recycling outlets to maximise the circular economy and sustainability outcomes. Hence, this study aims to propose a comprehensive list of evaluation criteria to rank recycling outlets, and develop an end-of-life tyre outlets selection matrix. A hybrid method is proposed by integrating fuzzy Analytical Hierarchy Process, fuzzy Technique of Order Preference Similarity to the Ideal Solution, the multi-objective linear programming, and semi-structured interviews. By analysing the empirical data collected from one of the largest European collectors, this study reveals that cement manufacturing, which is the primary recycling outlet, ranks the lowest among the five recycling outlets in terms of the circular economy and sustainability outcome. Nevertheless, synthetic turf manufacturing and moulded objects manufacturing rank the highest in the circular economy and sustainability outcomes, respectively. It is proved that cost and profit are key drivers for recycling outlets selection, subjected to end consumers' perceptions and the ease of end-of-life tyre processing. The ranking and the performance of recycling outlets also signify the competitive relationship between the circular economy and sustainability as excelling in the circular economy outcome would trade-off sustainability performance.

关键词： Circular economy Sustainability multi criteria decision making Fuzzy AHP-TOPSIS multi objective programming

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Accounting for uncertainty in eco-efficient agri-food supply chains: A case study for mushroom production planning

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JOURNAL OF CLEANER PRODUCTION 2019年 216卷 249-256页

作者： Banasik, Aleksander Kanellopoulos, Argyris Bloemhof-Ruwaard, Jacqueline M. Claassen, G. D. H. Wageningen Univ Operat Res & Logist Hollandseweg 1 NL-6706 KN Wageningen Netherlands

Due to the increasing awareness of climate change, depletion of natural resources, and increasing world population, companies in the agri-food sector need to redesign their existing supply chains and take into account both the economic and environmental impact of their operations. In practice not all the required information is available in advance due to various sources of uncertainty in agri-food supply chains. In this research a multi-objective two-stage stochastic programming model is proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in agri-food supply chains. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. The results of the optimizations show that accounting for stochasticity in important model parameters can reduce the difference between expected and realized economic performance by approximately 4% on average. Moreover, this paper demonstrates that including stochastic model parameters can reduce the environmental impact without compromising the current economic performance. Given the assumptions in the setup of the case study and the available information, it is concluded that applying a 2-stage stochastic programming approach for production planning decisions can lead to improved economic and environmental performance in an agri-food supply chain. New findings in real-life case studies are needed to get profound insights and understanding on the impact of uncertainty on production planning decisions in sustainable agri-food supply chains. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： multi objective programming Green supply chain management Sustainability Scenario based two-stage stochastic programming

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Bayesian step stress accelerated degradation testing design: A multi-objective Pareto-optimal approach

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2018年 171卷 9-17页

作者： Li, Xiaoyang Hu, Yuqing Zhou, Jiandong Li, Xiang Kang, Rui Beihang Univ Sch Reliabil & Syst Engn Sci & Technol Reliabil & Environm Engn Lab Beijing 100191 Peoples R China City Univ Hong Kong Coll Business Dept Management Sci Hong Kong Hong Kong Peoples R China Beijing Univ Chem Technol Sch Econ & Management Beijing 100029 Peoples R China Aberystwyth Univ Dept Comp Sci Aberystwyth Dyfed Wales

Step-stress accelerated degradation testing (SSADT) aims to access the reliability of products in a short time. Bayesian optimal design provides an effective alternative to capture parameters uncertainty, which has been widely employed in SSADT design by optimizing specified utility objective. However, there exist several utility objectives in Bayesian SSADT design;for the engineers, it causes much difficulty to choose the right utility specification with the budget consideration. In this study the problem is formulated as a multi-objective model motivated by the concept of Pareto optimization, which involves three objectives of maximizing the Kullback-Leibler (KL) divergence, minimizing the quadratic loss function of p-quantile lifetime at usage condition, and minimizing the test cost, simultaneously, in which the product degradation path is described by an inverse Gaussian (IG) process. The formulated programming is solved by NSGA-II to generate the Pareto of optimal solutions, which are further optimally reduced to gain a pruned Pareto set by data envelopment analysis (DEA) for engineering practice. The effectiveness of the proposed methodologies and solution method are experimentally illustrated by electrical connector's SSADT. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Reliability Bayesian optimal design Step stress accelerated degradation testing multi objective programming NSGA II DEA

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A proposed model for solving fuzzy linear fractional programming problem: Numerical Point of View

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JOURNAL OF COMPUTATIONAL SCIENCE 2018年 25卷 367-375页

作者： Das, Sapan Kumar Edalatpanah, S. A. Mandal, T. Natl Inst Technol Jamshedpur Dept Math Jamshedpur Jharkhand India Ayandegan Inst Higher Educ Dept Appl Math Tonekabon Iran

In solving real life fractional programming problem we often face the state of uncertainty as well as hesitation due to various uncontrollable factors. To overcome these limitations, the fuzzy logic approach is applied to this problem. In this paper, we propose the concepts of simple ranking approach between two triangular fuzzy numbers. We also formulate an equivalent tri-objective linear fractional programming problem to calculate the upper, middle and lower bounds of the Fuzzy Linear Fractional programming (FLFP) problem. Furthermore, from the obtained upper, middle and lower bounds, we construct the optimal values numerically. Finally, the effectiveness of the proposed procedure is illustrated through numerical and real life examples. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Triangular fuzzy number Linear fractional programming problem multi objective programming Ranking function

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Benchmarking bank branches : A dynamic DEA approach

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JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES 2021年第6期42卷 1203-1236页

作者： Razipour-GhalehJough, Somayeh Lotfi, Farhad Hosseinzadeh Rostamy-Malkhalifeh, Mohsen Sharafi, Hamid Islamic Azad Univ Dept Math Sci & Res Branch Tehran Iran

Nowadays, appraisal of performance, benchmark identification and determining policies for the survival of the organization is of interest to managers. Data Envelopment Analysis is a method for performing assessments, including the recognition of efficient decision making units and introducing benchmarks for the inefficient ones. Sometimes, the performance of organizations not only depends on the period under evaluation alone, but is also under the influence of production of the former periods. In this paper, a dynamic DEA model is presented to evaluate bank branches, when there are dependence between different time periods. The proposed model is applied for one of Iranian commercial banks and benchmarks which shows the shortest path to efficiency frontier are recognized.

关键词： Data envelopment analysis Dynamic DEA Target setting Benchmarking multi objective programming

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