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An Interval Fuzzy, Double-Sided, chance-constrained stochastic programming Model for Planning the Ecological Service Value of Interconnected River Systems

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WATER 2020年第9期12卷 2649-2649页

作者： Yang, Luze Cong, Weiyi Meng, Chong Cai, Baofeng Liu, Miao Jilin Univ Coll New Energy & Environm Changchun 130012 Peoples R China Environm Sci Res Inst Jilin Changchun 130012 Peoples R China Beijing Normal Univ Sch Environm State Key Lab Water Environm Simulat Beijing 100875 Peoples R China Dept Ecol & Environm Jilin Changchun 130012 Peoples R China

The western region of Jilin Province is an ecologically fragile area with scarce water resources. The effective allocation of the limited water resources in order to obtain a higher ecological service value is an urgent requirement. In this paper, an interval fuzzy, double-sided chance-constrained, stochastic programming (IFDCP) model was used based on the interconnected river system network project in the western Jilin Province. With the objective of maximizing the value of regional ecological services, the water diversion and supplement schemes were optimized and adjusted. The model results showed that the restored water surface area of all lakes and ponds in the western region of Jilin Province was higher than the initially planned scheme in the high flow year. The water surface area fulfilled the minimum constraints, but did not fulfill the initial scheme in the normal flow year. In the low flow year, the lower limit of some of the regions had to be decreased in order to meet the allocation of the limited water resources. The proportion of floodwater resource utilization gradually increased with an increase in the flood amount. The ecological service value produced in the normal and high flow years was found to be higher than the initial scheme. The marsh wetland can produce higher ecological service value. Therefore, the core of the model optimization was introducing more water to the marsh wetland after fulfilling the basic consumption of ponds and the reed wetland. In addition, the IFDCP model was more flexible in water diversion and supplement as compared to other models that had been developed previously.

关键词： interval fuzzy double-sided chance-constrained stochastic programming ecological services water diversion and supplement

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Capacity planning to cope with demand surges in fourth-party logistics networks under chance-constrained service levels

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COMPUTERS & OPERATIONS RESEARCH 2025年 176卷

作者： Jiang, Songchen Huang, Min Liu, Yunan Zhang, Yuxin Wang, Xingwei Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China North Carolina State Univ Dept Ind & Syst Engn Raleigh NC 27695 USA Northeastern Univ Coll Comp Sci & Engn Shenyang 110169 Peoples R China

In this paper, we study a capacity planning problem fora fourth-party logistics network (4PLN) in the face of event-triggered demand surges. We aim to solve a stochastic optimization problem in order to minimize the total cost for the 4PLN under chance-constrained service-level targets, where the stochastic demand process is modeled as a summation of random variables with a Bernoulli term of jump processes. At the heart of our solution procedure is a greedy pricing and weighting strategy based cell-and-bound (G-C&B) algorithm designed for solving the SAA-based model. Compared to the standard C&B method, our G-C&B is able to largely reduce the number of non-essential cell enumerations and achieve reduced running time complexity. To mitigate the performance degradation due to large system scale and/or sample instance, we extend our base algorithm to a two-step L ocal E xperimentation for G lobal O ptimization strategy based cell-and-bound (LEGO-C&B) framework, in which we first solve a small-scale training problem to find the important scenarios (eliminating excessive cell enumerations) and then use the training results to expedite the full optimization problem. We evaluate the performance of our algorithms by conducting a comprehensive series of numerical experiments. Besides, our results also demonstrate how the effectiveness of our methods depends on various factors including (i) the algorithm's hyperparameters such as the sample size and training ratio, and (ii) the 4PLN's input parameters such as the network scale, surge demand frequency, and rental price of 3PL resource. Our results exhibit several qualitative insights.

关键词： Logistics 4PL network capacity planning Demand surge chance-constrained stochastic programming Local experimentation for global optimization (LEGO) framework

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chance-constrained co-expansion planning for power systems under decision-dependent wind power uncertainty

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IET RENEWABLE POWER GENERATION 2023年第6期17卷 1342-1357页

作者： Yin, Wenqian Feng, Shuanglei Liu, Rong-Peng Hou, Yunhe Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China HKU Shenzhen Inst Res & Innovat Shenzhen Peoples R China China Elect Power Res Inst Renewable Energy Res Ctr Beijing Peoples R China

Variability and uncertainty in wind resources pose significant challenges to the expansion planning of wind farms and associated flexible resources. In addition, the spatial smoothing effect, indicating the impact of wind farm scale on aggregated wind power prediction errors, further aggravates the challenge. This paper proposes a chance-constrained co-expansion planning method considering the spatial smoothing effect, where the expansion of wind farm capacity, batter energy storage capacity, and power transmission lines are co-optimized. Specifically, a decision-dependent uncertainty (DDU) model is established capturing the dependency of wind power uncertainties on wind farm expansion decisions under the spatial smoothing effect. Unlike traditional optimization diagram where decisions are made under only decision-independent uncertainty (DIU) with fixe properties, properties of decision-dependent uncertain parameters would be inversely altered by decisions. To effectively tackle the coupling relation between decisions and DDU, DDU-based chance constraints are formulated in an analytical manner, where the decisions and decision-dependent uncertain parameters are expressed in a closed form. Eventually, with piecewise linearization of the DDU model and the polynomial approximation of cumulative distribution function of uncertain parameters, the proposed chance-constrained optimization model with DDU is converted into a mixed-integer second-order cone program (MISOCP). Case studies verify the effectiveness of the proposed method.

关键词： chance-constrained stochastic programming decision-dependent uncertainty expansion planning mixed-integer second-order cone programming power-generation planning power transmission planning programming stochastic wind power wind power generation

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The new approaches for solving hierarchical Chinese postman problem with stochastic travel times

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023年第5期44卷 8471-8492页

作者： Sokmen, Ozlem Comakli Yilmaz, Mustafa Erzurum Tech Univ Career Planning Applicat & Res Ctr Erzurum Turkiye Ataturk Univ Ind Engn Dept Erzurum Turkiye

The hierarchical Chinese postman problem (HCPP) aims to find the shortest tour or tours by passing through the arcs classified according to precedence relationship. HCPP, which has a wide application area in real-life problems such as shovel snow and routing patrol vehicles where precedence relations are important, belongs to the NP-hard problem class. In real-life problems, travel time between the two locations in city traffic varies due to reasons such as traffic jam, weather conditions, etc. Therefore, travel times are uncertain. In this study, HCPP was handled with the chance-constrained stochastic programming approach, and a new type of problem, the hierarchical Chinese postman problem with stochastic travel times, was introduced. Due to the NP-hard nature of the problem, the developed mathematical model with stochastic parameter values cannot find proper solutions in large-size problems within the appropriate time interval. Therefore, two new solution approaches, a heuristic method based on the Greedy Search algorithm and a meta-heuristic method based on ant colony optimization were proposed in this study. These new algorithms were tested on modified benchmark instances and randomly generated problem instances with 817 edges. The performance of algorithms was compared in terms of solution quality and computational time.

关键词： Optimization arc routing problems chance-constrained stochastic programming new efficient algorithm hierarchical Chinese postman problem

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A case-oriented computational study for sustainable fleet planning in a battery closed-loop supply chain network under uncertainty

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ENGINEERING COMPUTATIONS 2023年第7/8期40卷 1947-2008页

作者： Subulan, Kemal Baykasoglu, Adil Dokuz Eylul Univ Dept Ind Engn Izmir Turkiye

Purpose - The purpose of this study is to develop a holistic optimization model for an integrated sustainable fleet planning and closed-loop supply chain (CLSC) network design problem under uncertainty. Design/methodology/approach - A novel mixed-integer programming model that is able to consider interactions between vehicle fleet planning and CLSC network design problems is first developed. Uncertainties of the product demand and return fractions of the end-of-life products are handled by a chance-constrained stochastic program. Several Pareto optimal solutions are generated for the conflicting sustainability objectives via compromise and fuzzy goal programming (FGP) approaches. Findings - The proposed model is tested on a real-life lead/acid battery recovery system. By using the proposed model, sustainable fleet plans that provide a smaller fleet size, fewer empty vehicle repositions, minimal CO2 emissions, maximal vehicle safety ratings and minimal injury/illness incidence rate of transport accidents are generated. Furthermore, an environmentally and socially conscious CLSC network with maximal job creation in the less developed regions, minimal lost days resulting from the work's damages during manufacturing/recycling operations and maximal collection/recovery of end-of-life products is also designed. Originality/value - Unlike the classical network design models, vehicle fleet planning decisions such as fleet sizing/composition, fleet assignment, vehicle inventory control, empty repositioning, etc. are also considered while designing a sustainable CLSC network. In addition to sustainability indicators in the network design, sustainability factors in fleet management are also handled. To the best of the authors' knowledge, there is no similar paper in the literature that proposes such a holistic optimization model for integrated sustainable fleet planning and CLSC network design.

关键词： Sustainability Fleet management Closed-loop supply chain network design Mixed-integer programming Multi-objective optimization chance-constrained stochastic programming

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Humanitarian relief network design: Responsiveness maximization and a case study of Typhoon Rammasun

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IISE TRANSACTIONS 2023年第3期55卷 301-313页

作者： Shu, Jia Song, Miao Wang, Beilun Yang, Jing Zhu, Shaowen Univ Elect Sci & Technol China Sch Management & Econ Chengdu Peoples R China Hong Kong Polytech Univ Fac Business Dept Logist & Maritime Studies Hong Kong Peoples R China Southeast Univ Sch Comp Sci & Engn Nanjing Peoples R China Southeast Univ Sch Econ & Management Dept Management Sci & Engn Nanjing Peoples R China Natl Univ Singapore Chongqing Res Inst Modern Logist Ctr Chongqing Peoples R China

In this article, we study a humanitarian relief network design problem, where the demand for relief supplies in each affected area is uncertain and can be met by more than one relief facility. Given a certain cost budget, we simultaneously optimize the decisions of relief facility location, inventory pre-positioning, and relief facility to affected area assignment so as to maximize the responsiveness. The problem is formulated as a chance-constrained stochastic programming model in which a joint chance constraint is utilized to measure the responsiveness of the humanitarian relief network. We approximate the proposed model by another model with chance constraints, which can be solved based on two settings of the demand information in each affected area: (i) the demand distribution is given;and (ii) the partial demand information, e.g., the mean, the variance, and the support, is given. We use a case study of the 2014 Typhoon Rammasun to illustrate the application of the model. Computational results demonstrate the effectiveness of the solution approaches and show that the chance-constrained stochastic programming models are superior to the deterministic model for humanitarian relief network design.

关键词： Responsiveness maximization humanitarian relief network design chance-constrained stochastic programming

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Fourth-party logistics network design with demand surge: A greedy scenario-reduction and scenario-price based decomposition algorithm

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2024年 269卷

作者： Jiang, Songchen Huang, Min Zhang, Yuxin Wang, Xingwei Fang, Shu-Cherng Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ Coll Comp Sci & Engn Shenyang 110169 Liaoning Peoples R China North Carolina State Univ Edward P Fitts Dept Ind & Syst Engn Raleigh NC 27695 USA

The sharing economy has offered new viable approaches for firms to tackle demand surges. In this paper, we study a novel network design problem for the fourth -party logistics network (4PLN) to cope with unpredictable demand surges, in which temporary renting of logistics resources from a sharing market is available to supplement network capacity. A chance -constrained stochastic programming model is established to minimize the overall cost for 4PLN under service level targets. To deal with the difficulties brought by the evaluation of service level, we reformulate a mixed -integer linear programming (MILP) model, that can be solved straightly, based on the sample average approximation method. Then, to address the enormous challenge posed by the coupling of the basic NP -hard network design problem and the large number of demand scenarios in the MILP version, the Scenario -Price based Decomposition Algorithm (P -DA) is designed based on the key idea of decomposing the above -coupled factors. Further, to mitigate the performance deterioration brought on by large system scale and/or sample size, we expand our base algorithm to the Greedy Scenario -Reduction and Scenario -Price based Decomposition Algorithm (GR&P-DA) through the fast processing of chance constraints by introducing a greedy method. Through computational experiments, we demonstrate the effectiveness of our proposed model and algorithms, and we analyze the impact of various model parameters, including demand level, surge magnitude, surge probability, and rental price of third -party logistics resources, on 4PLN design. Furthermore, our comparative analysis reveals that renting logistics resources to address demand surges can significantly reduce costs and discovers that deploying resources in advance does not always provide an advantage, a temporary "case-by-case"planning approach for renting will give a more cost -saving scheme when surge probability is at a low level as it avoids idle resources by not b

关键词： Fourth-party logistics network (4PLN) design Unpredictable demand surge Service level chance-constrained stochastic programming Decomposition algorithm

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Two-Stage chance-constrained stochastic Thermal Unit Commitment for Optimal Provision of Virtual Inertia in Wind-Storage Systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2021年第4期36卷 3520-3530页

作者： Ding, Tao Zeng, Ziyu Qu, Ming Catalao, Joao P. S. Shahidehpour, Mohammad Xi An Jiao Tong Univ Dept Elect Engn Xian 710049 Peoples R China Univ Porto FEUP Fac Engn P-3784200 Porto Portugal INESC TEC P-3784200 Porto Portugal Illinois Inst Technol ECE Dept Chicago IL 60616 USA

The frequency security problem becomes a critical concern in power systems when the system inertia is lowered due to the high penetration of renewable energy sources (RESs). A wind-storage system (WSS) controlled by power electronics can provide the virtual inertia to guarantee the fast frequency response after a disturbance. However, the provision of virtual inertia might be affected by the variability of wind power generation. To address this concern, we propose a two-stage chance-constrained stochastic optimization (TSCCSO) model to find the optimal thermal unit commitment (i.e., economic operation) and the optimal placement of virtual inertia (i.e., frequency stability) in a power grid using representative power system operation scenarios. An enhanced bilinear Benders decomposition method is employed with strong valid cuts to effectively solve the proposed optimization model. Numerical results on a practical power system show the effectiveness of the proposed model and solution method.

关键词： Power system stability Wind farms Time-frequency analysis Security stochastic processes Frequency control Thermal stability Virtual inertia bilinear Benders decomposition chance-constrained stochastic programming renewable energy

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chance-constrained Multiple Bin Packing Problem with an Application to Operating Room Planning

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INFORMS JOURNAL ON COMPUTING 2021年第4期33卷 1661-1677页

作者： Wang, Shanshan Li, Jinlin Mehrotra, Sanjay Beijing Inst Technol Dept Management Sci & Engn Beijing 100081 Peoples R China Northwestern Univ Dept Ind Engn & Management Sci Evanston IL 60208 USA

We study the chance-constrained bin packing problem, with an application to hospital operating room planning. The bin packing problem allocates items of random sizes that follow a discrete distribution to a set of bins with limited capacity, while minimizing the total cost. The bin capacity constraints are satisfied with a given probability. We investigate a big-M and a 0-1 bilinear formulation of this problem. We analyze the bilinear structure of the formulation and use the lifting techniques to identify cover, clique, and projection inequalities to strengthen the formulation. We show that in certain cases these inequalities are facet-defining for a bilinear knapsack constraint that arises in the reformulation. An extensive computational study is conducted for the operating room planning problem that minimizes the number of open operating rooms. The computational tests are performed using problems generated based on real data from a hospital. A lowerbound improvement heuristic is combined with the cuts proposed in this paper in a branch-and-cut framework. The computations illustrate that the techniques developed in this paper can significantly improve the performance of the branch-and-cut method. Problems with up to 1,000 scenarios are solved to optimality in less than an hour. A safe approximation based on conditional value at risk (CVaR) is also solved. The computations show that the CVaR approximation typically leaves a gap of one operating room (e.g., six instead of five) to satisfy the chance constraint.

关键词： chance-constrained stochastic programming bin packing bilinear integer program branch-and-cut valid inequalities operating room planning

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Humanitarian relief network design: Responsiveness maximization and a case study of Typhoon Rammasun

A I I E Transactions

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A I I E Transactions 2023年第3期55卷 301-313页

作者： Jia Shu Miao Song Beilun Wang Jing Yang Shaowen Zhu a School of Management and Economics University of Electronic Science and Technology of China Chengdu China b Department of Logistics and Maritime Studies Faculty of Business The Hong Kong Polytechnic University Hong Kong China c School of Computer Science and Engineering Southeast University Nanjing China d Department of Management Science and Engineering School of Economics and Management Southeast University Nanjing China d Department of Management Science and Engineering School of Economics and Management Southeast University Nanjing Chinae Modern Logistics Center National University of Singapore (Chongqing) Research Institute Chongqing China

In this article, we study a humanitarian relief network design problem, where the demand for relief supplies in each affected area is uncertain and can be met by more than one relief facility. Given a certain cost budget, we simultaneously optimize the decisions of relief facility location, inventory pre-positioning, and relief facility to affected area assignment so as to maximize the responsiveness. The problem is formulated as a chance-constrained stochastic programming model in which a joint chance constraint is utilized to measure the responsiveness of the humanitarian relief network. We approximate the proposed model by another model with chance constraints, which can be solved based on two settings of the demand information in each affected area: (i) the demand distribution is given; and (ii) the partial demand information, e.g., the mean, the variance, and the support, is given. We use a case study of the 2014 Typhoon Rammasun to illustrate the application of the model. Computational results demonstrate the effectiveness of the solution approaches and show that the chance-constrained stochastic programming models are superior to the deterministic model for humanitarian relief network design.

关键词： Responsiveness maximization humanitarian relief network design chance-constrained stochastic programming

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