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

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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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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Optimization of water resource dispatching for Huanghua Port under uncertain water usage scenario

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SCIENCE OF THE TOTAL ENVIRONMENT 2021年 751卷 141597-141597页

作者： Fang, Yong Wang, Yanjiao Liu, Qiang Luo, Kan Liu, Zhonghua Beijing Univ Chem Technol Sch Econ & Management Beijing 100029 Peoples R China State Energy Grp Huanghua Port Co Ltd Informat Ctr Huanghua 061113 Hebei Peoples R China

In recent years, large-scale coal bulk cargo ports have been vigorously promoting the green and intelligent construction, it is an important problem for them to manage water resources scientifically and effectively to realize energy conservation and environmental protection under uncertain circumstances. Taking Huanghua Port of Shenhua Group in China as an example, firstly, through a systematic review of the water resource dispatching infrastructures and production operations, the four-level water resource dispatching framework of Huanghua Port was obtained. Secondly, an uncertain multi-objective programming model is constructed to comprehensively consider the cost of water purchase, the energy consumption of water diversion, and the uncertainty of water usage. Then, an algorithm is designed according to the characteristics of the model. Finally, the applicability and effectiveness of the water resource dispatching framework, optimization model, and solution algorithm are verified by the analysis of 8 typical production water scenarios. This study not only provides Huanghua Port with a water resource dispatching optimization solution but also provides a decision-making reference for the green and intelligent transformation and upgrading of other large-scale coal bulk ports. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Water resource dispatching Uncertainty multi-objective programming Decision-making support Huanghua Port

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Developing a two-stage model for a sustainable closed-loop supply chain with pricing and advertising decisions

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JOURNAL OF CLEANER PRODUCTION 2021年 309卷 127165-127165页

作者： Khorshidvand, Behrooz Soleimani, Hamed Sibdari, Soheil Esfahani, Mir Mehdi Seyyed Islamic Azad Univ Qazvin Branch Fac Ind & Mech Engn Qazvin Iran Univ Melbourne Sch Math & Stat Parkville Vic 3010 Australia Univ Massachusetts Charlton Coll Business Dartmouth MA USA Amirkabir Univ Technol Fac Ind Engn & Management Syst Tehran Polytech Tehran Iran

Closed-Loop Supply Chain (CLSC) has become a critical problem due to its effects on various factors including economic motivations, environmental concerns, and social impacts. Moreover, there are coordination tools, such as pricing and advertising, which impact its performance. In this paper, we offer a two-stage approach to model and solve a sustainable CLSC, taking into account pricing, green quality, and advertising. In the first stage, optimal decisions on pricing, greening, and advertising are made, while in the second stage, a fuzzy multiobjective Mixed Integer Linear programming (MILP) model is used to maximize the total profit, reduce CO2 emissions, and improve social impacts. Suitable solution methods are introduced according to the scale of the problem. For small-scale instances, an augmented epsilon-constraint method is used to solve the problem. For largescale instances, approximations are required, and a Lagrangian relaxation algorithm solves the problem in polynomial time. The performance of the proposed model is evaluated through various numerical examples. The results illustrate the applicability and efficiency of the model, while confirming significant improvements in sustainable objectives under optimal pricing, green quality, and advertising. Besides, the proposed Lagrangian relaxation method significantly reduces the computational time for large-scale instances, with only a 2.308% deviation from the optimal results.

关键词： Sustainable closed-loop supply chain multi-objective programming Supply chain pricing Augmented epsilon-constraint Lagrangian relaxation CO2 emissions

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Research on the Recovery of Irregular Flights under Uncertain Conditions

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World Journal of Engineering and Technology 2021年第4期9卷 755-764页

作者： Xiangfei Meng Xiaoyu Lin Hualei Zhao Jing Yang Department of Service Supporting Air Force Command College Beijing China

This paper mainly studies the problem of irregular flights recovery under uncertain conditions. Based on the analysis of the uncertain factors affecting the flight, taking the total delay time and the total cost of flight delay as the objective function, and considering the constraints of flight plan and passenger journey, an uncertain objective programming model is constructed. Finally, taking OVS airport temporarily closed due to bad weather as an example, the results show that better quality optimization scheme can be obtained by integrating passenger recovery with narrow sense flight recovery stage and implementing integrated recovery.

关键词： Recovery of Irregular Flights Uncertainty Theory multi-objective programming

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multi-period portfolio optimization using coherent fuzzy numbers in a credibilistic environment

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 167卷 114135-114135页

作者： Gupta, Pankaj Mehlawat, Mukesh Kumar Khan, Ahmad Zaman Univ Delhi Dept Operat Res Delhi 110007 India

In this paper, we use an extension of fuzzy numbers, called coherent fuzzy numbers, to model asset returns and an investor's perception of the stock market (pessimistic, optimistic, or neutral) simultaneously. Two multi-period multi-objective portfolio optimization models are formulated using mean absolute semi-deviation and Conditional Value-at-Risk (CVaR) as risk measures, respectively. We aim to provide more flexibility to the investor in specifying the risk tolerance and devise optimum investment plans for different investment horizons. The proposed models also incorporate bound, cardinality, and skewness constraints for each investment period to capture various stock market scenarios. A real-coded genetic algorithm is employed to solve the resultant models. Two real-life case studies involving 20 assets of the National Stock Exchange (NSE), India, and another involving 50 assets listed in the S&P 500 and NASDAQ-100 indexes have been provided to illustrate the efficacy and advantages of the models. An in-sample and out-of-sample analysis have been done for both the models to analyze the performance in the real-world scenario. The conclusion drawn from the analysis strongly emphasizes on accurately assessing the current stock market prospects, i.e., adopting the right attitude (pessimistic, optimistic, or neutral), is of paramount importance and must be included in the portfolio optimization problem.

关键词： Fuzzy multi-period portfolio optimization multi-objective programming Fuzzy set theory Coherent fuzzy numbers Conditional Value-at-Risk Real-coded genetic algorithm

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Stochastic energy management in a renewable energy-based microgrid considering demand response program

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 129卷 106791-106791页

作者： Hajiamoosha, Pouria Rastgou, Abdollah Bahramara, Salah Sadati, S. Muhammad Bagher Islamic Azad Univ Dept Elect Engn Kermanshah Branch Kermanshah Iran Islamic Azad Univ Dept Elect Engn Sanandaj Branch Sanandaj Iran

Climate changes increase concerns about global warming caused by greenhouse gases and have also increased the focus and implementation of renewable energy sources (RESs) planning. One of the important RESs is tidal energy or tidal power, which is a form of hydropower that converts the energy obtained from tides into the electrical power. Although tidal power is still not widely used, this energy resource has the potential for the future electricity generation. This paper addresses the stochastic energy management in a microgrid considering RESs such as solar, wind and tidal sources in the presence of the demand response program and storage devices. The uncertainty of the RESs, demand, and electricity price is handled by Monte Carlo simulation (MCS). The model is a linear multi-objective optimization which the first objective aims to reduce the cost and the second aims to reduce the emission. Augmented ?-constraint approach is applied to solve the problem in the CPLEX/ GAMS software environment. The interactive fuzzy decision-making is applied to choose the best answer among the Pareto answers according to the planner criteria.

关键词： multi-objective programming Tidal energy Renewable energy sources Augmented ?-constraint method Pollution emission

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Slotting Optimization of Distribution Center for Agriculture Products Considering ＂Freshness＂ under Traceable Cold Chain

World Scientific Research Journal

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World Scientific Research Journal 2021年第5期7卷 19-31页

作者： Haimei Zhang Weijiong Chen

With the rapid development of logistics, trade, and people's pursuit of health, the demand for fresh and safe fresh products is increasing, and logistics providers are facing great challenges. Distribution is an important part of fresh food delivery from the origin to the dining table, and its operation efficiency and service level are very important. Since the actual freshness of fresh products will be different due to the different operation conditions of different logistics links from the origin to the cold storage of distribution center, the purpose of this study is to explore the freshness evaluation method of fresh products, and to optimize the operation of the distribution center in the later stage by tracing the logistics operation information in the early stage. First of all, for a fresh product, the concentration of CO_2 in the closed environment at different temperatures was measured. The respiration rate was calculated, and then the freshness decline rate of fresh products at different temperatures was obtained. Secondly, the system flow chart of fresh products from picking, packaging, precooling, transportation, loading and unloading and handling is constructed, and the freshness is taken as the system reliability. Through the information traceability of the early temperature and operation time, the freshness rating of fresh products before warehousing is completed based on GO-FLOW method. Finally, taking the overall freshness, warehousing efficiency and shelf stability of cold storage as indicators, a multi-objective location optimization model is constructed, and the location allocation scheme is obtained through NSGA-II algorithm, which makes it more convenient for ＂perishable and perishable＂ fresh products and fresh products with high turnover rate. This paper provides a new idea for fresh product freshness rating and fresh product distribution center location optimization research, which is of great significance for improving fresh product freshnes

关键词： Freshness rating GO‐FLOW multi-objective programming Location optimization NSGA-II

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Eco-innovation analysis: A data envelopment analysis methodology

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ENVIRONMENTAL TECHNOLOGY & INNOVATION 2021年 23卷

作者： Arman, H. Jamshidi, A. Hadi-Vencheh, A. Islamic Azad Univ Najafabad Branch Dept Management Najafabad Iran Islamic Azad Univ Isfahan Khorasgan Branch Dept Math Esfahan Iran

The examination of financial development and environmental effect has driven inquiry into creating assessment models on environmental and economic changes, particularly on eco-innovation goods. Here, a new approach is proposed to find the common set of weights (CSWs) in data envelopment analysis (DEA) to examine the eco-innovation in the presence of undesirable factors. For this purpose, first, the current models are reviewed and criticized, and their shortcomings are clarified. Then, a simple way is proposed to find CSWs in DEA. We show the proposed approach leads to a better solution compared to current methods in the literature. Finally, the proposed model is applied to the eco-innovation analysis of OECD countries. Our findings show that the Czech Republic has the highest rank in eco-innovation. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Data envelopment analysis (DEA) Common set of weights (CSW) Efficiency multi-objective programming Eco-innovation

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A proposed method for third-party reverse logistics partner selection and order allocation in the cellphone industry

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 162卷

作者： Jauhar, Sunil Kumar Amin, Saman Hassanzadeh Zolfagharinia, Hossein Indian Inst Management Kashipur Operat Management & Decis Sci Kashipur India Ryerson Univ Ted Rogers Sch Management 575 Bay St Toronto ON Canada Ryerson Univ Dept Mech & Ind Engn Toronto ON Canada Indian Inst Management Kashipur India Ryerson Univ Toronto ON Canada

There are growing social and government pressures that encourage end of life (EOL) electronic products companies to focus on reverse logistics (RL) and recovery options. The complexity of RL elements for EOL electronic products is a challenge in this field. Recently, original equipment manufacturers (OEMs) have focused on RL activities. To this aim, third-party reverse logistics partners (3PRLPs) play an important role. This paper simultaneously draws attention to the selection of 3PRLPs and determine how orders are assigned to every 3PRLP using a new framework. There are two phases in this framework. The first phase includes an approach that integrates data envelopment analysis (DEA) with a differential evolution (DE) algorithm to increase the discriminatory power and distinguish the 3PRLPs based on their efficiencies. DEA is considered in this study because it is an effective method to determine the efficiency based on the simultaneous analysis of inputs and outputs. In Phase 2, those efficiency scores are utilized to allocate orders to 3PRLPs using a multi-objective model. Two solution approaches are employed for solving the proposed multi-objective model and to find Pareto-optimal solutions. The application of the models is shown in Canada's cellphone industry. The results reveal that the efficiency of 3PRLPs may have an effect on both third-party reverse logistics partner selection and the orders allocated to them.

关键词： Third-party reverse logistics partners (3PRLPs) Data envelopment analysis (DEA) multi-objective programming Reverse logistics (RL)

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