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Stochastic two-stage multi-objective unit commitment of distributed resource energy systems considering uncertainties and unit failures

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 253卷

作者： Liu, Jingfan Zhang, Shijie Chinese Acad Sci Inst Engn Thermophys Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Compared to centralized generation technology, distributed energy resource systems are susceptible to energy risks caused by boundary uncertainties and unit failures. This study introduces a stochastic two-stage multi- objective optimization method to address reliability-based unit commitment issues. In the day-ahead stage, operational state and reserve capacity are determined to minimize prescheduled operation costs based on forecasted parameters. In the real-time stage, a decision-dependent stochastic reliability method is proposed to simulate outage scenarios. Reserve resources within available units are allocated to mitigate forecasting errors and unit failures. Additionally, the grid interaction ratio and penalty cost are added to restrict the depth and frequency access to the grid. Four comparative cases analyze the effects of the proposed methodology. This method innovatively achieves the simulation of stochastic multi-unit outages and delete faulty units in the operation scheme. The optimal results show that the risks of electricity and cooling supply are underestimated, while the risks of heating are overestimated, compared to N-1 reliability. Furthermore, Pareto analysis of the multi-objective problem enhances independent operational capacity through utilization of reserve resources. Grid dispatch pressure is reduced since purchased power can be used as day-ahead planning. Thus, the methodology achieves collaborative optimization of reliability with a reduction of operation costs, offering effective guidance for engineering applications.

关键词： Distributed energy resource system Uncertainties and outages Stochastic two-stage UC Energy and reserve scheduling multi-objective programming

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Production, investment and financial plan for a "natural gas+" integrated energy enterprise: An assessment using system dynamics and multi-objective optimization model

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ENERGY REPORTS 2025年 13卷 1859-1874页

作者： Xiong, Ye Wang, Yifan Zhang, Yue Chen, Jieke Wu, Mengxi PetroChina Southwest Oil & Gasfield Co Res Inst Nat Gas Econ Chengdu Sichuan Peoples R China Chengdu Environm Protect Agcy Chengdu Sichuan Peoples R China Univ Leeds Business Sch Leeds England

This study explores the critical challenge of balancing energy supply, investment efficiency, and profitability during the transition of natural gas enterprises into "natural gas+ " integrated energy systems. In a dynamic and uncertain environment, these systems face competing objectives: the carbon neutrality, resource optimization, and financial sustainability. To address these complexities, this study proposes a System Dynamics-multi- objective programming (SD-MOP) model, grounded in the "Business-Production-Investment-Financial-Target" (BPIFT) framework, to integrate production, investment, and financial planning. The model incorporates SD to capture dynamic feedback among production, investment, and financial processes;MOP to resolve conflicting goals;Monte Carlo simulations to assess uncertainties across 200 scenarios;and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to generate Pareto-optimal solutions. Results identify key variables, such as the Reserve Replacement Ratio (RRR) and Single Well Production (SWP), as critical for maintaining system stability. Scenario analyses demonstrate that the model balances competing objectives, achieving a 14% improvement in energy supply and a 19% increase in profitability, while highlighting the trade-offs between maximizing energy supply and profitability under manageable investment levels. Overall, these findings establish the model as a practical decision-making tool for integrated energy enterprises, aligning enterprise strategies with sustainability goals.

关键词： Natural Gas+ Integrated Energy Enterprise System dynamics multi-objective programming Comprehensive planning Carbon neutrality Optimization Energy transition

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Active-Passive Beamforming Optimization for RIS-Aided mmWave Joint Localization and Communication System

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第2期74卷 2941-2957页

作者： Qiu, Hengji Gong, Shiqi Liu, Heng Zhao, Xin Xing, Chengwen Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Beijing Inst Technol Sch Cyberspace Sci & Technol Beijing 100081 Peoples R China Samsung Res China Beijing SRC B Beijing 100028 Peoples R China

With the remarkable development of the location-aware communications, joint localization and communication (L&C) has become one of the strongest competitors for the 6G key enabling technologies. Meanwhile, the reconfigurable intelligent surface (RIS) has emerged as an important enhancing technology for both communication and localization. In this paper, we investigate a RIS-aided joint L&C system, where the localization and data transmission functions are integrated in a time-division pattern. Specifically, we aim to jointly optimize the covariance matrices of the localization signal and the communication signal, the RIS beamforming matrix and the time division ratio to simultaneously improve the localization and communication performance. An alternating optimization (AO) algorithm is proposed via jointly leveraging the successive convex approximation technique, the semidefinite relaxation method and the projected gradient descent with momentum algorithm, based on which we strike a compelling trade-off between the localization and communication performance. Considering the high computational cost in the large-scale array scenario, we also develop a low-complexity algorithm free of iterations. To analyze the optimality of our proposed AO algorithm, we further consider the special single-user line-of-sight (LoS) scenario and validate that our AO algorithm could achieve the beam alignment, implying its effectiveness. Finally, numerical simulations are carried out to demonstrate the superior performance of our proposed algorithm.

关键词： Location awareness Optimization Array signal processing Millimeter wave communication Communication systems Resource management Performance evaluation OFDM Covariance matrices Wireless communication Joint localization and communication reconfigurable intelligent surface multi-objective programming successive convex approximation

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Biform game consensus analysis of group decision making with unconnected social network

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2025年第1期324卷 259-275页

作者： Tang, Jie Li, Zi-Jun Meng, Fan-Yong Gong, Zai-Wu Pedrycz, Witold Nanjing Univ Informat Sci & Technol Sch Management Sci & Engn Nanjing 210044 Peoples R China Cent South Univ Sch Business Changsha 410083 Hunan Peoples R China North China Univ Water Resources & Elect Power Sch Management & Econ Zhengzhou 450000 Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada

In today's network era, people's decisions are susceptibly influenced by others, especially the ones they trust. This study confines to studying social network group decision making (SNGDM). Due to the mutual influence of consensus level and consensus adjustment among decision makers (DMs), this study utilizes biform game theory to propose an innovative consensus mechanism for facilitating group decision making with unconnected social networks. Specifically, in the context of a DM social network with multiple trust relationship-based connected components, we construct a multi-objective programming model to determine the consensus adjustment. Within each connected component, we employ the digraph game theory to study DMs' consensus adjustments, leveraging the directional and asymmetrical characteristics of trust-relationships. We then analyze the consensus adjustments of feasible DM coalitions using built optimization models and define the di-Myerson value. Additionally, we construct several axiomatic systems to show the rationality of consensus allocation results. We identify partial trust-relationships that increase the consensus adjustments of DMs as irrational, and design an algorithm to address them, thereby reducing the cost of consensus. Finally, we present a case study that showcases the real-world application of our new theoretical results. This is the first bi-form game consensus mechanism based on trust relationship for SNGDM.

关键词： Group decisions and negotiations Consensus analysis Biform game multi-objective programming Di-myerson value

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Linear fractional optimization over the efficient set of multi-objective integer quadratic problem

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RAIRO-OPERATIONS RESEARCH 2024年第1期58卷 741-758页

作者： Bencheikh, Ali Moulai, Mustapha USTHB Fac Math Dept Operat Res BP32 El Alia 16111 Algeria USTHB Fac Math LaROMaD Lab BP32 El Alia 16111 Algeria

In this paper, we introduce an exact algorithm for optimizing a linear fractional utility function over the efficient set of a multi objective integer quadratic problem. The algorithm is based on the "Branch and Cut" principle, which combines the branching process to ensure decision variables' integrity and efficient cuts built off the non-increasing gradients' directions of objective functions to eliminate inefficient integer solutions. The proposed approach accelerates the convergence to the efficient solution that optimizes the utility function. After presenting and describing the algorithm, a detailed didactic example is illustrated, followed by an experimental study to validate our approach and show computational costs.

关键词： multi-objective programming integer programming quadratic programming fractional programming branch and cut

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multi-objective optimisation model of a low-cost path to peaking carbon dioxide emissions and carbon neutrality in China

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SCIENCE OF THE TOTAL ENVIRONMENT 2024年 912卷 169386页

作者： Wang, Shen Wu, Jing Xiang, Mengyu Wang, Siyi Xie, Xuesong Lv, Lianhong Huang, Guohe Chinese Res Inst Environm Sci Beijing 100012 Peoples R China Univ Regina Inst Energy Environm & Sustainable Communities Regina SK S4S 7H9 Canada

A low-cost path system for achieving carbon neutrality in China was modelled using multi-objective programming by integrating industrial production, electric power, heating, transportation, and forest carbon sequestration. We aimed to minimise the total system cost, CO2 emissions, and air pollutants. The constraints included China's targets of peaking CO2 emissions before 2030;achieving carbon neutrality before 2060;ensuring industry, power, heating, and transportation supplies;promoting green energy;and implementing emission control. The model accounted for industries with high coal consumption, such as steel and chemical industries. Various power sources were considered, including coal-fired, nuclear, wind, and solar energy. Forest carbon sink and carbon capture and storage technologies were employed to achieve the emission reduction goals. The model, which was validated using available research data, offered cost-effective path schemes and exhibited high validity. Our findings emphasise the importance of structural adjustments and emission control, with electric power, heating, and transportation sectors showing higher feasibility and providing greater contributions to achieving carbon neutrality than other industries. Conversely, industrial transformation in sectors such as iron and steel, chemical, and construction materials had low feasibility and limited contribution. The modelling outcomes provide valuable insights for developing low-cost, carbon emission-targeted transportation structures in China's complex system. The results presented here demonstrate the global applicability of this method in contributing to plans aimed at meeting key carbon reduction targets.

关键词： Peaking carbon dioxide emissions Carbon neutrality Low-cost path multi-objective programming Structure transportation Emission control

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Solving integer indefinite quadratic bilevel programs with multiple objectives at the upper level

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JOURNAL OF APPLIED MATHEMATICS AND COMPUTING 2024年第2期70卷 1153-1170页

作者： Fali, Fatima Cherfaoui, Yasmin Moulai, Mustapha USTHB Fac Math Dept Operat Res LaROMaD Lab PB 32 El Alia Algiers 16111 Algeria

Bilevel programming is characterized by the existence of two optimization problems in which the constraint region of the upper level problem is implicitly determined by the lower level optimization problem. This hierarchical design of optimization is suitable to model a large number of real-life applications. However, when dealing with a non linear multi-objective optimization context, new complexities arise due to conflicting objectives. In this paper, an exact method is described to solve an integer indefinite quadratic bilevel maximization problem with multiple objectives at the upper level, where the objective functions at both levels are the product of two linear functions. The algorithm suggested aims to produce a set of efficient solutions by employing a branch and cut approach. It optimizes the indefinite quadratic problem of the upper level within the feasible region of the original problem in an iterative manner. Then, it introduces the Dantzig cut technique to identify the optimal solution for the integer indefinite quadratic bilevel programming problem. Additionally, the algorithm utilizes an efficient cut that reduces the search process for obtaining the set of efficient solutions of the main problem, along with a branching constraint for the integer decision variables. The algorithm was implemented and tested on instances generated randomly, yielding positive outcomes.

关键词： multi-objective programming Bilevel programming Integer programming Quadratic programming Branch and cuts

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Collaborative Optimization of multi-Equipment Scheduling and Intersection Point Allocation for U-Shaped Automated Sea-Rail Intermodal Container Terminals

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 7373-7393页

作者： Wang, Xiaohan Jin, Zhihong Dalian Maritime Univ Coll Transportat Engn Dalian 116026 Peoples R China

Guided by green and low-carbon policies, the construction of intelligent container terminals is imperative. Based on the emerging U-shaped automated sea-rail intermodal container terminal (SRICT), this paper focuses on the collaborative optimization of multi-equipment scheduling and intersection point allocation considering direct and indirect transshipment modes. With the objectives of maximizing the balanced workload of bilateral-cantilever automated yard cranes (AYCs) and minimizing the invalid operation cost of the yard, a bi-objective programming model is formulated to determine the handling area for bilateral-cantilever AYCs, intersection points for direct transshipment containers, and scheduling schemes for bilateral-cantilever AYCs, automated guided vehicles (AGVs), and internal trucks (ITs). We employ Q-learning (QL) and cumulative prospect theory (CPT) based on multi-objective particle swarm optimization (MOPSO) to solve the model by guiding the search and adaptively adjusting parameters. By comparing evaluation indicators, we have verified that our algorithm is superior to the benchmark algorithms. We conducted comparative experiments on various repair operators and optimization strategies. Results indicate that the proposed model and algorithm can balance the workload of AYCs, reduce energy consumption, and improve handling efficiency. Note to Practitioners-This paper addresses the transshipment connection between ships, the yard, and trains. The U-shaped automated SRICT adopted a side-operation layout with more interaction points. Furthermore, due to constraints related to laying cables and the environment, automation technology has not fully covered all functional areas at the SRICT. Therefore, the new layout and semi-automation present a challenge for transferring sea-rail intermodal containers. This paper proposes a tailored model and algorithm for emerging automated SRICTs with bilateral-cantilever AYCs. The collaborative optimization of multi-equip

关键词： Containers Resource management Optimization Cranes Layout Collaboration Seaports Collaborative optimization U-shaped automated container terminal sea-rail intermodal transportation Q-learning multi-objective programming energy consumption intersection point

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A multi-objective closed loop supply chain design considering social responsibility, environmentally friendly materials and clean technology

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INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY 2025年 1-16页

作者： Seifbarghy, M. Partovi, F. Chattinnawat, W. Alzahra Univ Fac Engn Dept Ind Engn Tehran Iran Chiang Mai Univ Dept Ind Engn Chiang Mai Thailand

Closed-loop supply chains' roles in collecting and returning used products to the initial supply chain has attracted the attentions of many researchers. On the other hand, most of the researches only consider its economical dimension. In this research, for making sustainable decision, we have considered environmental and social dimensions, as well. For this reason, a novel multi-objective optimization model is proposed with hybrid centers in the chain. The economic objective is minimization of the total costs of opening new facilities and material movement along the chain. The environmental objective is maximization of the positive environmental measures including utilization of clean technology in collection centers and utilization of environmental friendly materials in production centers. The social aspect is maximization of the social effects of opening new facilities, especially as increased employment in the region and maximization of the corporate social responsibility level in the whole supply chain. Demand, return rate and some cost factors of the model are assumed to be uncertain. The well-known scenario-based programming is applied to tackle the uncertainties in the model. Suitable supply chains for the model given in this research are car tires, car parts and assemblies. The major finding of this research is bringing the addressed sustainability objectives in an integrated mathematical model.

关键词： Closed loop supply chain Network design multi-objective programming Social responsibility Environmentally friendly materials Clean technology

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Optimisation models for project selection in asset management: an application to the water sector

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2024年第5期31卷 2956-2987页

作者： Vilarinho, Hermilio Barbosa, Flavia Novoa, Henriqueta Silva, Jaime Gabriel Yamada, Luciana Camanho, Ana S. Univ Porto Fac Engn R Dr Roberto Frias P-4200465 Porto Portugal Inst Engn Sistemas & Comp Tecnol & Ciencia INESC T R Dr Roberto Frias Porto Portugal Aguas Douro & Paiva Rua Vilar 235 5 Andar P-4050626 Porto Portugal Inst Politecn Porto IPP Inst Super Engn Porto ISEP R Dr Antonio Bernardino Almeida 431 Porto Portugal

A significant challenge in asset management is the selection of investment projects for infrastructures, which often relies on subjective judgement and lacks structured decision support methods. This challenge is particularly complex in water systems due to the diverse and heterogeneous nature of the components requiring investment. While the infrastructure value index (IVI) is widely used to characterise assets and support investment decisions in the water sector, its application in optimisation models for generating efficient project portfolios remains unexplored. To address this research gap, this study introduces optimisation models for generating investment portfolio plans in water systems' asset management. The proposed approach includes two mixed-integer linear programming (MILP) models that determine optimal solutions and an evolutionary algorithm that offers sub-optimal alternative investment selection plans to provide decision-makers with additional choices for balancing optimal outcomes. The primary contribution of this research is the combined utilisation of MILP and evolutionary algorithms, integrating the IVI into the decision-making process. These tools provide decision-makers with structured methods for defining investment plans and minimising the subjective elements typically associated with such processes. To illustrate the effectiveness of the models, a case study is presented involving a pumping station of a Portuguese water company. The results demonstrate the practical application and benefits of the proposed approach in optimising investment decisions. This research contributes to advancing asset management practices by integrating quantitative optimisation techniques and leveraging the IVI, thereby enhancing the objectivity and efficiency of investment planning in water systems' asset management.

关键词： asset management capital investment planning project selection performance indicator mixed-integer linear programming multi-objective programming

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