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A robust multi-objective model for supporting agricultural water management with uncertain preferences

JOURNAL OF CLEANER PRODUCTION 2020年 255卷 120204-000页

作者： Zhang, Tianyuan Tan, Qian Zhang, Shan Wang, Shuping Gou, Tianyu China Agr Univ Coll Water Resources & Civil Engn Beijing 100083 Peoples R China Guangdong Univ Technol Inst Environm & Ecol Engn Guangzhou 510006 Peoples R China

Sustainable management of agricultural water resources is essential for promoting regional development and restoring ecological environment. Due to the imperfection of knowledge and imprecision of expression, the preferences of objectives are uncertain in nature. However, the uncertain feature of objective preferences is often neglected in solving multi-objective water management problems. Also, random information is prevalent in in the optimizaiton efforts of agricultural water management systems. Recognizing the needs to tackle uncertainty existing in both preferences over objectives and parameters of constraints, a new mathematical programming method named multi-objective chance-constrained programming approach for planning problems with uncertain weights (MCUW) was proposed. It could handle uncertain weights of objectives without known distributions, and quantify the risks of objective unattainability arising from such uncertainty. It could also deal with uncertain parameters with known probability distributions, generating solutions with varied risks of constraint violation. The proposed MCUW method was applied to a case study of agricultural water resources management problem in Northwest China to demonstrate its applicability. multiple sets of optimal solutions under different combinations of weights fluctuation ranges, protection levels, and surface water availabilities were obtained, providing management options for stakeholders with different risk appetites. Results indicate that the objective value would increase with higher risks of objective unattainability or water-shortage. The MCUW method was compared to two potential alternatives and deemed effective in balancing multiple objectives and tackling complex uncertainties. Monte Carlo simulation showed that the results of MCUW were more densely distributed than those obtained from the model with deterministic weights, verifying that the developed MCUW model could provide robust solutions when faced with

关键词： Agricultural water management Robust optimization multi-objective programming Weight uncertainty System risk

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Double recovery strategy of carbon for coal-to-power based on a multi with tradable certificates

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ENERGY 2023年第1期273卷

作者： Ma, Ning Fan, Lurong Xian Univ Technol Sch Econ & Management Xian 710054 Peoples R China Sichuan Univ Business Sch Chengdu 610064 Peoples R China Sichuan Univ Inst New Energy & Low Carbon Technol Chengdu PR Brazil

Coal production and consumption cause methane and carbon dioxide emissions. The high emission cost and the limited renewable energy in some areas restrict the low-carbon energy system development. This paper proposes a double recovery system based on a multi-energy system to promote energy efficiency and emission reduction, considering the life cycle carbon emissions of coal and carbon trading. A nonlinear multi-objective two-stage stochastic programming model and an approximate solution algorithm based on NSGA-II are built to find the economic-ecological balanced strategy for the system investment and operation under uncertainty. Finally, a case study about the collieries in Xianyang City is adopted to test the effectiveness of the proposed model and algorithm. The results show the multi-energy system with a double recovery system can obtain 5%-40% more profits compared with the single energy system when the GHG emission rate requirement is lower than 0.95kgCO2e/kwh. And this paper finds that carbon capture and storage has more universal utility in obtaining tradable green certificates, and the efficiency of P2G technology depends on the abundance of renewable energy. The tradable green certificates are effective incentives for coal mine methane utilization.

关键词： multi-energy production system Coal mine methane utilization Tradable green certificates Double recovery of carbon multi-objective programming Economic-ecological benefit balance

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On the spectrum of achievable targets in cross-efficiency evaluation and the associated secondary goal models

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 177卷 114927-114927页

作者： Davtalab-Olyaie, Mostafa Ghandi, Fatemeh Asgharian, Masoud Univ Kashan Fac Math Sci Dept Appl Math Kashan *** Iran McGill Univ Dept Math & Stat Burnside HallRoom 1224805 Sherbrooke St West Montreal PQ H3A 0B9 Canada

The cross-efficiency (CE) evaluation method was introduced to improve the discriminatory power of DEA and eliminate unrealistic DEA weighting schemes. One important issue in CE evaluation is the non-uniqueness of the CE scores. Several secondary goal models based on different targets for cross-efficiencies (CEs) of each DMU with respect to other DMUs were proposed to address this issue. However, the suggested targets, fixed value 1 and the CCR efficiency score, are not achievable for all CEs. Moreover, the proposed secondary goal models based on these targets are sensitive to outlier DMUs, and may generate unrealistic CE scores. In this manuscript, we prove that the spectrum of achievable targets of CEs can be obtained using the most resonated appreciative (MRA) model, proposed by Oral et al. (2015), and the least resonated appreciative (LRA) model that we introduce. To this end, we propose a general secondary goal model using multi-objective programming and show that the CEs generated using MRA (LRA) model for each DMU is greater (less) than the corresponding CEs obtained by any other model that can be derived from the proposed benevolent (aggressive) general model. Using this achievable spectrum, we then propose several benevolent, aggressive and neutral secondary goal, and a weighted average CE evaluation model. Using two real examples, we compare the results of the proposed CE methods with those obtained from several other CE methods. Our data analyses indicate that our proposed methods are less sensitive to outliers, less biased towards 1, has better discriminatory power and can identify pseudo-efficient DMUs.

关键词： Data envelopment analysis Cross-efficiency evaluation multi-objective programming Secondary goal model

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Landfill Location with Expansion Possibilities in Developing Countries

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2015年第2期22卷 292-300页

作者： Manyoma, Pablo Orejuela, Juan P. Torres, Patricia Marmolejo, Luis F. Vidal, Carlos J. Univ Valle Sch Ind Engn Santiago De Cali Colombia Univ Valle Sch Nat Resources & Environm Engn Santiago De Cali Colombia

Municipal Solid Waste Management (MSWM) has become one of the main challenges of urban areas in the world. For developing countries, this situation is of greater severity due to disordered population growth, rapid industrialization, and deficiency in regulations, among other factors. One component of MSWM is the final disposal, where landfills are the most commonly used technologies for this purpose. According to a body of research, landfill location should meet the needs of all stakeholders, thus we propose a model based on multi-objective programming considering several decisions such as landfill opening, when they should be opened, and especially a common situation in our countries: the kind of expansion capacity that should be used. We present an example that reflects the conflict of two objectives: cost and environmental risk. The results show the allocation of each municipality to each landfill and the amount of municipal solid waste to be sent, among other variables.

关键词： capacity expansion landfill location multi-objective programming municipal solid waste management undesirable facilities

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Conceptualising a supply and demand resilience methodology: A hybrid DEMATEL-TOPSIS-possibilistic multi-objective optimization approach

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 160卷 107589-107589页

作者： Mohammed, A. Naghshineh, B. Spiegler, V Carvalho, H. Muscat Univ Fac Transport & Logist Bldg 142 Muscat Oman Univ Kent Kent Business Sch Dept Analyt Operat & Syst Canterbury Kent England Univ NOVA Lisboa Fac Sci & Technol UNIDEMI Dept Mech & Ind Engn P-2829516 Caparica Portugal

Due to the growing globalisation and strategic sourcing, supply chains (SCs) are confronted with potential dis-ruptions. Companies need to make further efforts and investments to improve their supply chain resilience (SCR) in becoming more prepared to minimise disruption risks. Sourcing is one of the main, strategic, key factors towards SCR. Also, organisations require resilience in demand fulfilment to handle volatile marketplaces. This paper presents a methodology towards SCR to both supply and demand variations motivated by a real case study of a manufacturing company that works to improve its SCR. To this end, a hybrid integrated multi-attribute decision making-possibilistic bi-objective programming model (MADM-PBOPM) was developed. First, a new framework presenting pillars to assess suppliers' resilience was developed based on a thorough literature review and decision makers' input. Then, a DEMATEL-TOPSIS approach was proposed to quantify existing suppliers' resilience and assess its performance. It also helped in categorising resilience pillars (RPs) as causes and effects. Thereafter, the obtained weights of suppliers and pillars were integrated into the developed PBOPM. The latter helps the purchasing team to (1) order materials from suppliers based on their resilience and performance ef-ficiency;and (2) elevate the company's resilience to uncertain demands fulfilment. Therefore, the developed methodology can potentially be used by the purchasing teams to build up SCs that are resilient to supply disruption and demand uncertainty. This MADM-PBOPM model was validated as part of the case study inves-tigation. Furthermore, the suppliers' assessment output was validated by using two sensitivity analysis ap-proaches including criteria weight variation and other multi-attribute decision making (MADM) approaches.

关键词： COVID-19 disruption Resilient sourcing Supply chain resilience multi-objective programming MCDM

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multi-objective open location-routing model for relief distribution networks with split delivery and multi-mode transportation under uncertainty

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SCIENTIA IRANICA 2018年第6期25卷 3635-3653页

作者： Veysmoradi, D. Vahdani, B. Sartangi, M. Farhadi Mousavi, S. M. Islamic Azad Univ Fac Ind & Mech Engn Dept Ind Engn Qazvin Branch POB *** Qazvin Iran PNU Dept Ind Engn POB 19395-3697 Tehran Iran Shahed Univ Fac Engn Dept Ind Engn POB 18155-159 Tehran Iran

In this study, the response phase of the management of natural disasters is investigated. One of the important issues in this phase is determining the distribution areas and timely distributing relief to affected areas in which transportation routing is of critical importance. In the event of disasters, especially flood and earthquake, terrestrial transportation is not fairly easy due to the damage to many infrastructures. For this reason, we propose that delivering relief from the distribution areas to disaster stricken places should be done by terrestrial and aerial transportation modes, simultaneously, to increase route reliability and reduce travel time. In this study, for relief allocation after earthquake, we offer a mixed-integer nonlinear open location-routing model in uncertain condition. This model includes several contradictory objectives and a variety of factors such as travel time, total costs, and reliability. In order to solve this model, a hybrid solution by combining robust optimization and fuzzy multi-objective programming has been used. The performance and effectiveness of the offered model and solution approach have been investigated through a case study of earthquake in East Azerbaijan, Iran. Our computational results show that the solution we have offered for real problems is effective. (C) 2018 Sharif University of Technology. All rights reserved.

关键词： Emergency logistics Relief distribution Location Routing Split delivery multi-objective programming Robust optimization

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Integrating fleet replacement and pilot training schedules for airborne service helicopters

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JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2016年第6期39卷 653-665页

作者： Tang, Ching-Hui Huang, Hsin-Ta Natl Taiwan Ocean Univ Dept Transportat Sci Keelung Taiwan Kainan Univ Dept Air Transportat Taoyuan Taiwan

In this study, we examine an integrated problem involving fleet replacement and pilot training scheduling for airborne service helicopters. Two objectives, minimizing the total cost and the number of batches of pilot training, are considered based on the practical requirements. multi-objective programming combined with a time-space network technique is applied to solve the problem. Numerical tests, in reference to the operations of a Taiwanese organization, are carried out to demonstrate the performance of the proposed model. A comparison of the proposed model and two single-objective models corresponding to the two objectives is also presented.

关键词： Fleet replacement pilot training schedule multi-objective programming network model

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Project Time-Cost-Quality Trade-off Problem: A Novel Approach Based on Fuzzy Decision Making

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INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS 2020年第4期28卷 545-567页

作者： Keshavarz, Esmaeil Shoul, Abbas Islamic Azad Univ Dept Math Sirjan Branch Sirjan Iran Vali e Asr Univ Rafsanjan Fac Adm Sci & Econ Dept Ind Management Rafsanjan Iran

Trade-off problems concentrate on balancing the main parameters of a project as completion time, total cost and quality of activities. In this study, the problem of project time-cost-quality trade-off is formulated and solved from a new standpoint. For this purpose, completion time and crash cost of project are illustrated as fuzzy goals, also the dependency of implementing time of each activity and its execution-quality is described by a fuzzy number. The overall quality of the project execution is defined as the minimum execution-quality of the project activities that should be maximized. Based on some real assumptions, a three-objective programming problem associated with the time-costquality trade-off problem is formulated;then with the aim of identifying a fair and appropriate trade-off, the research problem is reformulated as a single objective linear programming by utilizing a fuzzy decision-making methodology. Generating a final preferred solution, rather than a set of Pareto optimal solutions, and having a reasonable interpretation are two most important advantages of the proposed approach. To explain the practical performance of the proposed models and approach, a time-cost-quality trade-off problem for a project with real data is solved and analyzed.

关键词： Project scheduling time-cost-quality trade-off multi-objective programming fuzzy decision making preferred solution

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Predictive multi-period multi-objective portfolio optimization based on higher order moments: Deep learning approach

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年第1期183卷

作者： Abolmakarem, Shaghayegh Abdi, Farshid Khalili-Damghani, Kaveh Didehkhani, Hosein Islamic Azad Univ Dept Ind Engn South Tehran Branch Tehran Iran Islamic Azad Univ Dept Ind Engn Aliabad Katoul Branch Aliabad Iran

We propose a multi-Period multi-objective Portfolio Optimization model (MPMOPO). We used deep-learning approach to predict future behavior of stock returns. We consider four objectives, i.e., wealth, variance, skewness, and kurtosis and several constraints such as cardinality, budget, upper and lower limits of purchase, and diversification to address real-world situations. The investor can rebalance the portfolio through daily trade by buying or selling subject to transaction costs. We applied the proposed method in a daily closing price prediction of six stocks from FTSE 100. Goal programming method was used to solve the models. The results of statistical analysis show the applicability and efficacy of the proposed method in comparison with those methods which used historical data to form the portfolio.

关键词： Long short-term memory Convolutional neural network Stock prediction multi-period portfolio optimization multi-objective programming Goal programming

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A robust convex optimization approach to design a hierarchical organ transplant network: A case study

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EXPERT SYSTEMS WITH APPLICATIONS 2022年第0期197卷 116716-116716页

作者： Rouhani, Samira Amin, Saman Hassanzadeh Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Ryerson Univ Dept Mech & Ind Engn Toronto ON Canada

Organ transplant network as one of the most complex and challenging networks among healthcare systems, requires an effective supply chain design. In this research, a novel bi-objective hierarchical location-allocation model is developed to design an organ transplant network. The goal is to simultaneously minimize the total time and costs, and maximize the geographic parity in the network under supply and demand uncertainty. Different transportation modes are considered in the developed network, and the optimum transportation mode is selected after solving the model. The augmented epsilon-constraint technique is applied to solve the multi-objective model. Furthermore, a convex robust optimization approach is developed to tackle uncertain nature of the parameters. Finally, a case study is presented and the optimal solutions of the developed models are calculated and analyzed.

关键词： Robust optimization Organ transplant network Healthcare management Facility Location multi-objective programming

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