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A 0-1 linear relaxation and stochastic approximation method for real-time pricing in a smart grid with non-convex constraints

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ENGINEERING OPTIMIZATION 2024年第12期56卷 2131-2147页

作者： Tao, Li Wang, Zongyao Su, Xia Huaiyin Inst Technol Fac Math & Phys Huaian Peoples R China

In this article, real-time pricing (RTP) for a smart grid with complicated non-convex and/or non-smooth constraints is explored. First, piecewise linear functions are adopted to approximate any kinds of utility function and RTP is formulated into bilevel non-convex programming. Then, a 0-1 relaxation method is used to linearize sparse constraints and piecewise linear utility functions, to obtain mixed integer linear programming. Finally, a distributed simultaneous perturbation stochastic approximation (DSPSA) method is designed to solve the bilevel non-convex programming. The RTP strategy is generalizable because sparse constraints and non-differentiable and/or non-concave utility functions are widespread in practice, and the piecewise linear functions approximation method is applicable to all kinds of utility function, not just to non-smooth and/or non-concave utility functions. In addition, the 0-1 linear relaxation and stochastic approximation method make the bilevel non-convex programming easily solvable by DSPSA, which converges rapidly while maintaining the high accuracy of solutions.

关键词： Smart grid real-time pricing 0-1 relaxation method mixed integer linear programming distributed simultaneous perturbation stochastic approximation

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Impact of limiting the ergonomic risk on the economic and productive efficiency of an assembly line

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2024年第1-2期62卷 122-140页

作者： Alfaro-Pozo, Rocio Bautista-Valhondo, Joaquin Univ Politecn Catalunya UPC Serv & Ind Robot Operat Prod & Enterprise SIR OPEDept Organitz Empreses D Inst Organitzac Control Sistemes Ind IOCEscola Te Barcelona Spain Univ Politecn Catalunya UPC Inst Organitz & Control Sistemes Ind IOC Serv & Ind Robot OperatEscola Tecn Super Engn Ind Prod & Enterprise SIR OPEDept Organitzac Empreses Ave Diagonal647 Barcelona 08028 Spain

Considering ergonomics at the design phase can lead to assembly lines that protect and improve workers' health and well-being. However, this may reduce efficiency and productivity. Evaluating the potential benefits of incorporating ergonomics into line design versus the additional costs associated with the number of extra stations required or increased idle time, as well as exploring other ergonomic design alternatives, is critical for decision-makers. An assembly line balancing problem considering time, space and ergonomics, is used to evaluate the impact of ergonomic considerations. A model for maximising line efficiency is proposed and linearised for solution by the solver CPLEX. The mixed-integer linear model is compared to an alternative linearisation approach in which a decision variable is parameterised and then iteratively solved. An example and a case study are used to observe the competitiveness of both solution methods, where the iterative approach is shown to be superior for real size problems. The results show that ergonomic evaluation in line design leads to safer but less productive lines, which in turn increases the number of workstations and costs. Specifically, limiting ergonomic risk to a moderate level for the engine assembly line examined in this study, means maximum daily drop of 27 engines.

关键词： Assembly line balancing efficiency ergonomics productivity mixed integer linear programming

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The United Kingdom electricity market mechanism: A tool for a battery energy storage system optimal dispatching

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RENEWABLE ENERGY 2024年 231卷

作者： Casella, Virginia La Fata, Alice Suzzi, Stefano Barbero, Giulia Barilli, Riccardo Univ Genoa Dept Informat Bioengn Robot & Syst Engn DIBRIS Genoa Italy Univ Genoa Elect & Telecommun Engn & Naval Architecture Dept Genoa Italy Renantis SpA Milan Italy

In this paper, the role of a Battery Energy Storage System (BESS) in the United Kingdom (UK) electricity market is investigated. Such device is selected since research works related to the topic demonstrate that BESSs help facing challenges caused by renewable energy sources increasing penetration in the power systems' field. Indeed, in the next future, BESSs will assume a relevant role thanks to their fast response time. In the present paper, an optimization model is implemented to encode the UK market rules and output the optimal set of offers on dayahead and intraday markets, dynamic frequency response services and imbalance settlement. The market rules are formalised in a mathematical model considering market temporal sequencing and BESS technical limitations. The tool also models the state of energy management, necessary since BESSs are energy limited assets. Objective function and constraints are linearized to define a mixed integer linear programming problem to reduce the computational burden and to integrate the model in the Energy Management System previously developed at University of Genoa. Specific tests are performed including and excluding ancillary services to evaluate the related advantages. The obtained outcomes reveal that ancillary services are the most convenient options within all the implemented scenarios.

关键词： Battery energy storage system Energy management system Electricity market mixed integer linear programming Dynamic frequency response services

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A novel model for transfer synchronization in transit networks and a Lagrangian-based heuristic solution method

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第1期317卷 76-91页

作者： Ansarilari, Zahra Bodur, Merve Shalaby, Amer Univ Toronto Dept Civil & Mineral Engn Toronto ON Canada Univ Edinburgh Sch Math Edinburgh Scotland

To realize the benefits of network connectivity in transfer -based transit networks, it is critical to minimize transfer disutility for passengers by synchronizing timetables of intersecting routes. We propose a mixedinteger linear programming timetable synchronization model that incorporates new features, such as dwell time determination and vehicle capacity consideration, which have been largely overlooked in the literature at the scheduling stage. We introduce a new concept of pre -planned holding time, called transfer buffer time, to reduce the transfer waiting time, particularly for transfers to low -frequency routes, while taking into account the penalty of extra in -vehicle time for onboard passengers and the possible consequences on headway regularity of a route. We develop a Lagrangian relaxation -based heuristic to obtain high -quality solutions efficiently for large instances. Our experiments on instances with up to 12 transfer nodes in the City of Toronto, with a mixture of low- and high -frequency routes, illustrate the potential benefits of the proposed model over the state of the art. The results indicate that incorporating transfer buffer time, dwell time determination, and vehicle capacity consideration improves model outcomes considerably, also demonstrating the computational efficiency of our Lagrangian-based solution method.

关键词： Transfer synchronization Bus dwell time determination Vehicle capacity mixed integer linear programming Lagrangian relaxation

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Ego-Network Segmentation via (Weighted) Jaccard Median

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2024年第9期36卷 4646-4663页

作者： Zhong, Haodi Loukides, Grigorios Conte, Alessio Pissis, Solon P. Xidian Univ Sch Comp Sci & Technol Xian 710071 Peoples R China Kings Coll London London WC2R2LS England Univ Pisa I-6126 Pisa Italy CWI NL-1098XG Amsterdam Netherlands Vrije Univ NL-1081HV Amsterdam Netherlands

An ego-network is a graph representing the interactions of a node (ego) with its neighbors and the interactions among those neighbors. A sequence of ego-networks having the same ego can thus model the evolution of these interactions over time. We introduce the problem of segmenting a sequence of ego-networks into k segments. Each segment is represented by a summary network, and the goal is to minimize the total loss of representing k segments by k summaries. The main challenge is to construct a summary with minimum loss. To address it, we employ the Jaccard Median (JM) problem, for which, however, no effective and efficient algorithms are known. We develop several algorithms for JM: (I) an exact algorithm, based on mixed integer linear programming;(II) exact and approximation polynomial-time algorithms for minimizing an upper bound of the objective function of JM;and (III) efficient heuristics. We also study a generalization of the segmentation problem, in which there may be multiple edges between a pair of nodes in an ego-network, and develop a series of algorithms (exact algorithms and heuristics) for it, based on a more general problem than JM, called Weighted Jaccard Median (WJM). By building upon the above results, we design algorithms for segmenting a sequence of ego-networks. Extensive experiments show that our algorithms produce (near)-optimal solutions to JM or to WJM and that they substantially outperform state-of-the-art methods which can be employed for ego-network segmentation.

关键词： Approximation algorithms Heuristic algorithms Social networking (online) Upper bound mixed integer linear programming linear programming Synthetic data Ego-network jaccard median segmentation

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Digital Twin-Driven Dynamic Scheduling of Flexible Manufacturing System in the Context of Smart Factory Producing Brass Accessories

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JOURNAL OF INDUSTRIAL INTEGRATION AND MANAGEMENT-INNOVATION AND ENTREPRENEURSHIP 2025年第1期10卷 67-107页

作者： Chakroun, Ayoub Hani, Yasmina Elmhamedi, Abderrahmane Masmoudi, Faouzi Univ Paris VIII Vincennes Univ Inst Technol Lab QUARTZ EA 7393 FR-93100 Montreuil France Univ Sfax Natl Sch Engineers Sfax Lab LA2MP Route Soukra Sfax 3038 Tunisia

This study aims to deal with a dynamic scheduling problem of a real Flow Shop follow-up of an assembly process considering the specific constraints and requirements of a brass accessories manufacturing (BAM) company. We basically set up a Digital Twin-driven dynamic scheduling approach for Industry 4.0 by addressing uncertainties of machine availability. In fact, the setup of this Digital Twin (DT) is the outcome of the combination of both optimization and simulation. For the first step, we have elaborated a mixed integer linear programming (MILP) scheduling model by taking into account the dedicated requisites of our case study. Concerning simulation, a 3D simulation platform of a workshop producing brass accessories controlled by a Cyber-Physical Production System (CPPS) has been developed, in our previous work, including constraints and stochastic aspects. The simulation constraints are difficult or impossible to be modeled in the MILP model. These designs are integrated with the real workshop to construct the Digital Twin. The proposed tool enables the rescheduling of production orders based on machine disturbances and unpredictability. Validation scenarios have been designed and conducted to highlight the efficacy of the Digital Twin approach utilizing the brass accessories case study. We are confident that this represents the initial endeavor addressing the optimization of production rescheduling in a flow shop follow-up of a mixed assembly system.

关键词： Dynamic scheduling flow shop assembly process digital twin Industry 4.0 flexibility machines availability mixed integer linear programming

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A Universal Cooperative Decision-Making Framework for Connected Autonomous Vehicles With Generic Road Topologies

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第4期74卷 5414-5429页

作者： Huang, Zhenmin Liu, Wenru Shen, Shaojie Ma, Jun Hong Kong Univ Sci & Technol Guangzhou Robot & Autonomous Syst Thrust Guangzhou 511453 Peoples R China Hong Kong Univ Sci & Technol Div Emerging Interdisciplinary Areas Hong Kong Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Peoples R China

Cooperative decision-making of Connected Autonomous Vehicles (CAVs) presents a longstanding challenge due to its inherent nonlinearity, non-convexity, and discrete characteristics, compounded by the diverse road topologies encountered in real-world traffic scenarios. The majority of current methodologies are only applicable to a single and specific scenario, predicated on scenario-specific assumptions. Consequently, their application in real-world environments is restricted by the innumerable nature of traffic scenarios. In this study, we propose a unified optimization approach that exhibits the potential to address cooperative decision-making problems related to traffic scenarios with generic road topologies. This development is grounded in the premise that the topologies of various traffic scenarios can be universally represented as Directed Acyclic Graphs (DAGs). Particularly, the reference paths and time profiles for all involved CAVs are determined in a fully cooperative manner, taking into account factors such as velocities, accelerations, conflict resolutions, and overall traffic efficiency. The cooperative decision-making of CAVs is approximated as a mixed-integer linear programming (MILP) problem building on the DAGs of road topologies. This favorably facilitates the use of standard numerical solvers and the global optimality can be attained through the optimization. Case studies corresponding to different multi-lane traffic scenarios featuring diverse topologies are scheduled as the test itineraries, and the efficacy of our proposed methodology is corroborated.

关键词： Decision making Topology Roads Optimization Games Merging Autonomous vehicles Trajectory planning Trajectory mixed integer linear programming Autonomous driving multi-agent systems connected autonomous vehicles (CAVs) cooperative decision-making non-convex optimization mixed-integer linear programming (MILP)

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Extensive Model and Matheuristic Algorithm for the Train Platforming Problem with Two-Train-Capacity Tracks: A Case Study of Prague Central Station

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TRANSPORTATION RESEARCH RECORD 2024年第4期2678卷 131-154页

作者： Ozer, Emine Akyol Bulicek, Josef Sarac, Tugba Eskisehir Tech Univ Ind Engn Dept Eskisehir Turkiye Univ Pardubice Dept Transport Technol & Control Pardubice Czech Republic Eskisehir Osmangazi Univ Ind Engn Dept Eskisehir Turkiye

This paper provides a deeper insight into the train platforming problem (TPP). Many studies have focused on different versions of train scheduling and routing problems, and most of them assume that the platform track's capacity is one train. However, especially in busy and complex railway stations, most platform tracks are divided into two parts, allowing two trains to simultaneously share the same platform track for passenger boarding/alighting. This results in more efficient train assignment to the platform tracks. In addition, consideration of the track capacity makes the problem more difficult because directions of trains are problematic. Motivated by this challenge, we consider the TPP with two-train-capacity tracks. We first describe the problem in detail and then propose a mixed-integer programming model. The objective of the considered problem is to minimize the total weighted train delays, which are defined as the difference between the departure times calculated by the mathematical model (M1) and the scheduled departure times of the trains in the timetable. Because of the NP-hard nature of the problem, the proposed M1 may not find feasible solutions for large-size problems. Thus, a matheuristic algorithm (MA) is developed to solve large-size problems. We used randomly generated test problems to demonstrate the performance of the proposed M1 and MA. Experimental results showed that MA outperforms M1 in both solution quality and solution time. Additionally, a case study was conducted at the central station of Prague, Czechia.

关键词： matheuristic algorithm passenger rail transportation mixed integer linear programming platform track assignment railway optimization models transportation planning analysis and application train platforming problem

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Coal Plant Retirement and Repurposing Optimization Model

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IEEE ACCESS 2024年 12卷 194122-194132页

作者： Chattopadhyay, Debabrata World Bank Energy & Extract Washington DC 20433 USA

Retirement and repurposing of coal-based generation plants is a critical part of the energy transition. While there are established planning models that comprehensively capture both capacity entry and exit decisions at a system level, there are certain nuances when it comes to coal retirement. Existing coal plants can be repurposed to switch fuel (e.g., biomass), or the site can repurposed to install renewable and energy storage facilities. There are other issues around stranded asset value of coal plants that still have productive life left, availability of financing and allocation of concessional finance for retirement and repurposing activities. There is currently no model/tool that can capture these issues to make balanced decisions on retirement and repurposing of coal generating units. The proposed modeling framework is developed to address coal (or any fossil fuel) fleetwide retirement and repurposing decisions cast as a multi-year mixed integer linear programming model taking into consideration technical, economic and policy considerations. It makes retirement and repurposing decisions at a generating unit level to maximize the net revenue for the entire fleet given a target generation level and/or CO2 emissions cap. Decision variables in the model include retirement decisions, repurposing options that maximize the value of the site, employment, finance structure and dispatch of coal units. The working of a prototype model has been illustrated using a set of simple examples.

关键词： Coal Retirement Biological system modeling Costs Generators Planning Low carbon economy Investment Analytical models Power system security Energy transition coal plant retirement repurposing of coal plants optimization model mixed integer linear programming

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Hierarchical Framework for Space Exploration Campaign Schedule Optimization

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JOURNAL OF SPACECRAFT AND ROCKETS 2024年第5期61卷 1146-1164页

作者： Gollins, Nicholas Ho, Koki Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta GA 30332 USA

Space exploration plans are becoming increasingly complex as public agencies and private companies target deep-space locations, such as cislunar space and beyond, which require long-duration missions and many supporting systems and payloads. Optimizing multimission exploration campaigns is challenging due to the large number of required launches as well as their sequencing and compatibility requirements, making conventional space logistics formulations unscalable. To tackle this challenge, this paper proposes an alternative approach that leverages a two-level hierarchical optimization algorithm: an evolutionary algorithm is used to explore the campaign scheduling solution space, and each of the solutions is then evaluated using a time-expanded multicommodity flow mixed-integer linear program. A number of case studies, focusing on the Artemis lunar exploration program, demonstrate how the method can be used to analyze potential campaign architectures. The method enables a potential mission planner to study the sensitivity of a campaign to program-level parameters such as logistics vehicle availability and performance, payload launch windows, and in situ resource utilization infrastructure efficiency.

关键词： Space Exploration and Technology Optimization Algorithm Space Logistics Models Lunar Exploration mixed integer linear programming Evolutionary Algorithm Propellant Mass Fraction Multi Objective Genetic Algorithm

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