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Designing Closed-Loop Supply Chain Network for High-Salvage Perishable Products Under Uncertain Environment

IEEE ACCESS 2021年 9卷 102236-102250页

作者： Yang, Yabin Chen, Yong Guangzhou Coll Technol & Business Sch Management Guangzhou 510850 Peoples R China Sun Yat Sen Univ Lingnan Univ Coll Guangzhou 510275 Peoples R China

High-salvage perishable products have the characteristics of a short life cycle and high residual value. To extract the maximum value of this kind of product, a closed-loop supply chain network model based on the product life cycle is constructed under various uncertainties. This model incorporates various assumptions such as multiple products, multiple periods, timeliness of recycling, and four-echelon supply chain including manufacturers, wholesalers, recycling centers, and consumer markets. Where the recovery cost and the reuse rate are denoted by interval numbers, the demand and the capacity are denoted by stochastic and fuzzy numbers respectively. A Two-step interactive method based on fuzzy flexible programming is used to handle the uncertainties. The optimum solutions in the harsh environment and favorable environment are obtained by a numerical example, and the results show the proposed method is more accurate in grey degree and more robust in site selection than the interval chance-constraint mixed-integer nonlinear programming method. Besides, we demonstrate the relationships between the sensitivity coefficients and the profits. i.e., the higher the probability of stockout in the secondary market, the harsher the external environment is, the stockout will get increasing, and the corresponding expected profit will get lower;inversely, the higher the degree of satisfaction in the e-commerce market, the more favorable the external environment is, the stockout will get decreasing, and the corresponding expected profit will get higher. Furthermore, the numerical simulation also shows that the price of recycled products fluctuates with the increase of the probability of no stockout, where the price fluctuation in the secondary market and the e-commerce market are fundamentally the same, while the price of parts fluctuates least. Finally, according to the results of the sensitivity analysis, some managerial insights are given in the conclusion.

关键词： Supply chains Uncertainty programming Stochastic processes Recycling Mathematical model Business Perishable products product life cycle closed-loop supply chain chance-constraint interval programming fuzzy flexible programming

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Robust Transient Stability Emergency Control Considering Wind Power Uncertainties

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IEEE ACCESS 2023年 11卷 35315-35326页

作者： Ma, Yunfei Wang, Xin Geng, Guangchao Jiang, Quanyuan Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China

Transient stability emergency control (TSEC) enhances power system transient stability during large disturbances but faces challenges in the high-penetration wind power grid where the wind power forecast error still cannot be ignored even with state-of-the-art forecasting methods. In this paper, the TSEC problem is modeled as robust nonlinear programming with the objective of maintaining rotor angle stability by generator tripping and load shedding while the uncertain wind power outputs are regarded as intervals. interval programming is employed to solve the robust TSEC problem where the trajectory sensitivity analysis is applied to approximate the bounds of transient stability constraints. Numerical results on two test systems demonstrate that the proposed method improves computational efficiency and shows good performance on robustness.

关键词： Power system stability Transient analysis Wind power generation Wind turbines Uncertainty Stability criteria Mathematical models interval programming trajectory sensitivity analysis transient stability emergency control wind power uncertainties worst case

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An interval-parameter fuzzy nonlinear optimization model for stream water quality management under uncertainty

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第3期180卷 1331-1357页

作者： Qin, X. S. Huang, G. H. Zeng, G. M. Chakma, A. Huang, Y. F. Univ Regina Fac Engn Regina SK S4S 0A2 Canada N China Elect Power Univ SinoCanada Ctr Energy & Environm Res Beijing 102206 Peoples R China Hunan Univ Dept Environm Sci & Engn Changsha 410082 Peoples R China Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada Tsing Hua Univ Inst River & Coastal Engn Beijing 100084 Peoples R China

Planning for water quality management systems is complicated by a variety of uncertainties and nonlinearities, where difficulties in formulating and solving the resulting inexact nonlinear optimization problems exist. With the purpose of tackling such difficulties, this paper presents the development of an interval-fuzzy nonlinear programming (IFNP) model for water quality management under uncertainty. Methods of interval and fuzzy programming were integrated within a general framework to address uncertainties in the left- and right-hand sides of the nonlinear constraints. Uncertainties in water quality, pollutant loading, and the system objective were reflected through the developed IFNP model. The method of piecewise linearization was developed for dealing with the nonlinearity of the objective function. A case study for water quality management planning in the Changsha section of the Xiangjiang River was then conducted for demonstrating applicability of the developed IFNP model. The results demonstrated that the accuracy of solutions through linearized method normally rises positively with the increase of linearization levels. It was also indicated that the proposed linearization method was effective in dealing with IFNP problems;uncertainties can be communicated into optimization process and generate reliable solutions for decision variables and objectives;the decision alternatives can be obtained by adjusting different combinations of the decision variables within their solution intervals. It also suggested that the linearized method should be used under detailed error analysis in tackling IFNP problems. (c) 2006 Elsevier B.V. All rights reserved.

关键词： environment interval programming fuzzy programming nonlinear optimization uncertainty linear programming

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interval transportation problem: feasibility, optimality and the worst optimal value

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2023年第3期31卷 769-790页

作者： Garajova, Elif Rada, Miroslav Charles Univ Prague Fac Math & Phys Dept Appl Math Malostranske Nam 25 Prague 11800 Czech Republic Prague Univ Econ & Business Fac Informat & Stat Dept Econometr Nam W Churchilla 4 Prague 13067 Czech Republic Prague Univ Econ & Business Fac Finance & Accounting Dept Financial Accounting & Auditing Nam W Churchilla 4 Prague 13067 Czech Republic

We consider the model of a transportation problem with the objective of finding a minimum-cost transportation plan for shipping a given commodity from a set of supply centers to the customers. Since the exact values of supply and demand and the exact transportation costs are not always available for real-world problems, we adopt the approach of interval programming to represent such uncertainty, resulting in the model of an interval transportation problem. The interval model assumes that lower and upper bounds on the data are given and the values can be independently perturbed within these bounds. In this paper, we provide an overview of conditions for checking basic properties of the interval transportation problems commonly studied in interval programming, such as weak and strong feasibility or optimality. We derive a condition for testing weak optimality of a solution in polynomial time by finding a suitable scenario of the problem. Further, we formulate a similar condition for testing strong optimality of a solution for transportation problems with interval supply and demand (and exact costs). Moreover, we also survey the results on computing the best and the worst optimal value. We build on an exact method for solving the NP-hard problem of computing the worst (finite) optimal value of the interval transportation problem based on a decomposition of the optimal solution set by complementary slackness. Finally, we conduct computational experiments to show that the method can be competitive with the state-of-the-art heuristic algorithms.

关键词： Transportation problem interval programming Optimal value

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An interval multistage water allocation model for crop different growth stages under inputs uncertainty

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AGRICULTURAL WATER MANAGEMENT 2017年 186卷 86-97页

作者： Chen, Shu Shao, Dongguo Gu, Wenquan Xu, Baoli Li, Haoxin Fang, Longzhang Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Peoples R China

Due to different responses of crop growth stages to the water deficit, it is necessary to optimize water allocation between different growth stages to obtain the maximum food production in reservoir irrigation systems which are widely distributed throughout Southern China and India. In order to address the inputs uncertainties and dynamics existing in the above agricultural water management, an interval multistage water allocation model is developed. By incorporating multistage stochastic programming and interval parameter programming, the developed model can deal with uncertain inputs both expressed as interval parameters and probability distributions, and realize a dynamic irrigation among different growth stages from a reservoir. In the model, water requirement targets are first treated as first-stage decision variables to tackle the unique problem of agricultural water management. Additionally, given that net benefit and penalty of each growth stage are key parameters due to their determinative roles for allocation between different growth stages, a crop water production function is introduced into the calculation to make them factually reflect the competition among different growth stages. The model is then applied to the Yangshudang Irrigation District to plan rice irrigation and demonstrate its applicability. Rainfall has been divided into five levels with probability distributions in each growth stage and parameters have been characterized as interval numbers to show system uncertainty. Five scenarios that represent different initial active storage levels of the reservoir are set to acquire more detailed results. Through the parameter estimation, net benefits are [1.08,1.29], [5.04, 6.01], [11.79,14.08] and [1.61,1.92] RMB/m(3), and penalties are [2.39, 2.48], [11.13, 11.54], [26.05, 27.01] and [3.55, 3.68] RMB/m(3) for tillering stage, booting stage, heading stage and milky stage respectively. Through the model simulation, water requirement targets in booti

关键词： Crop growth stage interval programming Irrigation water allocation Multistage stochastic programming Water production function Inputs uncertainty

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Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

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ENGINEERING OPTIMIZATION 2013年第6期45卷 745-765页

作者： Vahdani, Behnam Tavakkoli-Moghaddam, Reza Jolai, Fariborz Baboli, Arman Univ Tehran Coll Engn Dept Ind Engn Tehran Iran Inst Natl Sci Appl DISP Lab F-69621 Villeurbanne France

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.

关键词： closed loop supply chain network design reliability interval programming fuzzy possibilistic chance-constrained programming

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Decarbonization pathways for bulk vessels: Integrating power systems, fuels, and control measures

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OCEAN ENGINEERING 2024年 300卷

作者： Zhao, Yuzhe Ge, Rui Zhou, Jingmiao Notteboom, Theo Dalian Maritime Univ Collaborat Innovat Ctr Transport Studies Dalian 116026 Peoples R China Dalian Univ Foreign Languages Business Sch Dalian 116044 Peoples R China Univ Ghent Maritime Inst B-9000 Ghent Belgium Univ Antwerp Fac Business & Econ B-2000 Antwerp Belgium Antwerp Maritime Acad Fac Sci B-2030 Antwerp Belgium

The shipping industry must delineate feasible switching pathways of emission reduction technologies for vessels if it wants to meet the emission reduction targets set forth by the International Maritime Organization (IMO). This paper introduces a programming model integrating power systems, alternative fuels, and air emission control measures to decarbonize bulk vessel operations. The model captures the uncertainty in fuel prices and carbon emission prices. Reliable decision-making schemes are generated using interval quadratic programming. The results reveal that power systems will switch from mono-fuel internal combustion engines (MF ICE) to dualfuel internal combustion engines (DF ICE). Traditional fossil fuels will progressively give way to carbon-neutral alternatives. The combination of air emission control measures will markedly reduce emissions.

关键词： Bulk vessels Decarbonization pathway Power systems and alternative fuels Air emission control measures interval programming

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A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty

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APPLIED ENERGY 2010年第3期87卷 1033-1047页

作者： Chen, W. T. Li, Y. P. Huang, G. H. Chen, X. Li, Y. F. Peking Univ Lab Earth Surface Proc Coll Urban & Environm Sci Beijing 100871 Peoples R China N China Elect Power Univ Energy & Environm Res Ctr Beijing 102206 Peoples R China Univ Regina Environm Syst Engn Program Fac Engn Regina SK S4S 0A2 Canada Chinese Acad Sci Key Lab Oasis Ecol & Desert Environm Xinjiang Inst Ecol & Geog Urumqi 830011 Xinjiang Peoples R China

In this study, a two-stage inexact-stochastic programming (TISP) method is developed for planning carbon dioxide (CO2) emission trading under uncertainty. The developed TISP incorporates techniques of interval-parameter programming (IPP) and two-stage stochastic programming (TSP) within a general optimization framework. The TISP can not only tackle uncertainties expressed as probabilistic distributions and discrete intervals, but also provide an effective linkage between the pre-regulated greenhouse gas (GHG) management policies and the associated economic implications. The developed method is applied to a case study of energy systems and CO2 emission trading planning under uncertainty. The results indicate that reasonable solutions have been generated. They can be used for generating decision alternatives and thus help decision makers identify desired GHG abatement policies under various economic and system-reliability constraints. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Carbon dioxide Energy interval programming Stochastic Two-stage Trading Uncertainty

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Long-term panning of waste diversion under interval and probabilistic uncertainties

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RESOURCES CONSERVATION AND RECYCLING 2010年第7期54卷 449-461页

作者： Sue, J. Huang, G. H. Xi, B. D. Qin, X. S. Huo, S. L. Jiang, Y. H. Chen, X. R. Univ Regina Fac Engn Regina SK S4S 0A2 Canada Beijing Normal Univ Sch Environm Beijing 100875 Peoples R China Chinese Res Inst Environm Sci Beijing 100012 Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn Singapore 639798 Singapore

An inexact chance-constraint mixed integer linear programming (ICMILP) model was proposed for supporting long-term planning of waste management in the City of Foshan, China. The presented model took waste generation, collection, transportation and treatment processes into consideration, and was specifically designed to reflect the practical situations of waste management in Chinese cities. Three special characteristics of the developed method made it unique compared with the other optimization techniques that deal with uncertainties. Firstly, it provided a linkage to pre-regulated policies that had to be respected when a modeling effort was undertaken;secondly, it was useful for tackling uncertainties presented as intervals probabilities;thirdly, it could facilitate dynamic analysis for decisions of facility expansions within a multi-facility, multi-period, multi-level, and multi-option context. Three scenarios were considered based on various combinations of financial capability and environmental demand. The results indicate that the city would attain a relatively low diversion rate if its waste management practices continue to be based on the existing policy over 15 years. However, higher diversion rates associated with lower system cost would be achieved if the City's policy is to be based on an aggressive capacity-expansion plan for composting and incinerating facilities. The model solutions would be valuable for supporting the long-term capacity planning for waste-management facilities as well as the formulation of policies regarding waste generation, diversion and management. (C) 2009 Elsevier B.V. All rights reserved.

关键词： interval programming Decision making Chance-constraint Waste management Uncertainty Environment

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Inexact credibility constrained programming for environmental system management

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RESOURCES CONSERVATION AND RECYCLING 2011年第4期55卷 441-447页

作者： Zhang, Yi Mei Huang, Guo He Univ Regina Fac Engn Environm Syst Engn Program Regina SK S4S 0A2 Canada Univ Regina Fac Engn & Appl Sci Environm Syst Engn Program Regina SK S4S 0A2 Canada

This study proposed an inexact credibility constrained programming (ICCP) to deal with multi-formats of uncertainties in parameters and variables for an agricultural water planning system. The study system includes three subareas with different crop distributions. The redundant water in the wet season can be stored in the reservoir and utilized in the dry season. The ICCP method can reflect not only inexact uncertainties in the objective function, variables and parameters, but also fuzzy uncertainties in the right-hand side. interval credibility levels which represent satisfaction degrees of the constraints can be analyzed. Scenario analysis is conducted to analyze possible events in wet and dry years. The resulting solutions can provide stable intervals for the objective function and decision variables with different levels of risk when violating the constraints. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Credibility Water resource Reservoir Water conversation interval programming Agricultural Fuzzy

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