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Network-level optimisation approach for bridge interventions scheduling

STRUCTURE AND INFRASTRUCTURE ENGINEERING 2024年

作者： Mendoza-Lugo, Miguel Angel Nogal, Maria Morales-Napoles, Oswaldo Delft Univ Technol Dept Hydraul Engn Delft Netherlands Delft Univ Technol Dept Mat Mech Management & Design Delft Netherlands

This paper introduces a novel extension of the multi-system optimisation method, known as the 3C concept, tailored for optimising budget allocation for bridge interventions at the network level. This extended methodology accounts for the interdependencies among bridges due to their spatial proximity within the network. It incorporates direct and user costs, bridge performance indicators, and a bridge deterioration model. A real-world case study involving a portfolio of 555 bridges demonstrates the practicality of the methodology, efficiently determining the optimal intervention sequence. Over an 18-year analysis period, the proposed methodology achieved a 23% reduction in total costs by combining repairs for bridges with high to severe damage and maintenance for the others. This represents a significant improvement compared to the traditional approach, used by bridge management agencies, which relies exclusively on maintenance. The optimised procedure outperforms human intuition in managing complex bridge networks, particularly over extended periods. This methodology can assist transportation agencies in implementing and exploring various scenarios by adjusting the time between consecutive interventions and budget constraints, supporting comprehensive analysis and informed decision-making.

关键词： Bridge network interventions maintenance repair mixed-integer linear programming optimisation multi-system

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Home energy management system for residential fuel cell-based combined heat and power system

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JOURNAL OF BUILDING ENGINEERING 2024年 98卷

作者： Teo, J. C. Yao, Leehter Natl Taipei Univ Technol Dept Elect Engn Taipei 10608 Taiwan

The goal of this paper is to propose an optimization scheme for enhancing power dispatch and load scheduling for residential fuel cell-based combined heat and power systems (FC-CHPS) using mixed integer linear programming (MILP), considering the lifetime degradation of both the fuel cell system (FCS) and battery energy storage systems (BESS). The scheme is applied in the home energy management system that oversees the electric and thermal power of residential FC-CHPS. First, the nonlinearity in the relationship between the natural gas consumption and output electric power, and between the residual thermal power and output electric power of the fuel cell system (FCS) in the FC-CHPS is approximated using piecewise linearization. Then, the piecewise linearization is integrated with MILP to derive optimal power dispatch and load scheduling solutions, while accounting for the nonlinearity of the FCS. Next, cost functions representing the lifetime degradation of FCS and BESS are formulated. These cost functions result in nonlinear optimization constraints. Therefore, innovative methods are proposed to linearize these constraints, allowing the continued use of MILP as the optimization method and factoring in the lifetime degradation of FCS and BESS. Compared to the mixed-integer non-linear programming (MINLP) method that does not linearize the non-linearity in the FCS or the lifetime degradation of the FCS and BESS, the proposed MILP scheme achieves the identical objective function value. Furthermore, the computation time for the proposed MILP scheme is 99.94 % lower than that required by the MINLP method. The proposed scheme provides accurate results in short computation times.

关键词： Combined heat and power Fuel cell systems Home energy management system mixed-integer linear programming Piecewise linearization

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Effects on dimensioning of heat supply technologies for district heating under consideration of future developments regarding investment costs and emission factors

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ENERGY 2024年 301卷

作者： Divkovic, Denis Knorr, Lukas Schwesig, Ramon Meschede, Henning Paderborn Univ Dept Energy Syst Technol Paderborn Germany

Municipalities and energy suppliers are facing the challenge of transforming space heating supply from fossil fuels to energy sources with low greenhouse gas emissions as part of the heating sector transition. Redesigning and planning future heat generation portfolios for district heating networks involves uncertainties such as energy prices, investment costs, district heat sales, and building energy efficiency. This study presents an optimisation model based on multi-objective mixed-integer linear programming to address economic and ecological needs. The model considers economic and emission objectives to find optimal solutions for heat generation unit dimensioning under different growth scenarios and different emission factors for district heat demands. The results show different pareto optimal solutions, providing a range for heat generation unit dimensioning and heat generation over the investigated time horizon. Additionally, the results include commissioning timepoints which are compared within different heat demand growth scenarios.

关键词： District heating Multi-objective optimisation mixed-integer linear programming Commissioning timepoints

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Optimal management in island microgrids using D-FACTS devices with large-scale two-population algorithm

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Energy Informatics 2024年第1期7卷 1-35页

作者： Khademi, Mohamad Mehdi Samiei Moghaddam, Mahmoud Davarzani, Reza Azarfar, Azita Hoseini, Mohamad Mehdi Department of Electrical Engineering Shahrood Branch Islamic Azad University Shahrood Iran Department of Electrical Engineering Damghan Branch Islamic Azad University Damghan Iran

Amidst the increasing complexity of microgrid optimization, characterized by numerous decision variables and intricate non-linear relationships, there is a pressing need for highly efficient algorithms. This study introduces a tailored mixed integer Nonlinear programming (MINLP) model that optimizes the charging and discharging schedules of electric vehicles (EVs) and energy storage systems (ESS) while incorporating Distributed Flexible AC Transmission System (D-FACTS) devices. To address these challenges, a novel approach based on the Large-Scale Two-Population Algorithm (LSTPA) is proposed. The model's effectiveness was evaluated using a 33-node microgrid, where the proposed method achieved a total purchased energy of 1.2 MWh, a voltage deviation of 0.0357 p.u, and a CPU time of 551 s, outperforming traditional methods like NSGA-II, PSO, and JAYA. Additionally, in a 69-node microgrid, the approach resulted in a total purchased energy of 0.3 MWh and a voltage deviation of 0.0078 p.u. These results demonstrate the superior performance of the proposed method in terms of energy efficiency, voltage stability, and computational time, advancing the efficiency of microgrid management. © The Author(s) 2024.

关键词： mixed-integer linear programming

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A distributionally robust approach for the two-machine permutation flow shop scheduling

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ANNALS OF OPERATIONS RESEARCH 2024年第1期338卷 709-739页

作者： Lu, Haimin Pei, Zhi Zhejiang Univ Technol Coll Mech Engn Hangzhou 310023 Peoples R China

We consider the two-machine permutation flow shop scheduling problem with uncertain job processing time, which is sampled from no specific distribution type. For the ease of discussion, an ambiguity set with a priori mean and support set information is constructed. We then introduce a distributionally robust optimization (DRO) perspective to handle the uncertainty. To the best of our knowledge, this is the first time that a DRO method is applied to this problem setting. Given that the original DRO model is nonlinear and intractable in nature, we first reformulate the inner maximization problem into a linear programming model with a fixed sequence, based on the duality theory and optimality conditions. By including the sequence decision, we further transform it into an equivalent mixed-integer linear programming (MILP) problem via incorporating the valid lower and upper bounds and McCormick inequalities. The obtained MILP could be solved to optimality with the off-the-shelf commercial solvers. In the numerical study, it is demonstrated that the DRO-based model could effectively solve the large scale instances with up to 100 jobs optimally within 30 s. Compared with the SLP, DRO model always triumphs on the worst-case indicator. And as the problem scale increases, the DRO model gradually outperforms the SLP in terms of the Up-90% and Up-75% indicators. Furthermore, the optimal sequence obtained by the deterministic model is less stable than the DRO model, which can enhance the robustness of the manufacturing system against processing uncertainty.

关键词： Scheduling Flow shop Distributionally robust optimization mixed-integer linear programming

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Mathematical programming models for order picking in warehouses with decoupling of picker and cart

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS 2024年第1期11卷

作者： Zha, Junjie Du, Donglei Zhu, Xi Li, Meixia Tianjin Univ Technol Sch Management 91 Bin Shui Xi Dao Rd Tianjin 300384 Peoples R China Fuzhou Univ Sch Econ & Management Fuzhou Peoples R China Univ New Brunswick Fac Management Fredericton NB Canada Tianjin City Vocat Coll Dept Basic Educ Tianjin Peoples R China

As a special Travelling Salesman Problem (TSP), the Single-Picker Routing Problem (SPRP) in warehouses is of important theoretical and practical significance. In manual order picking, the items are usually picked up by a picker with a cart. To speed up the picking process, the picker is allowed to stop the cart to pick up the items individually and return to the location of the cart. This paper proposes a mixed integer linear programming formulation for an order picking problem with the decoupling of the picker and the cart in a multi-block warehouse, where the picker capacity is at most four. And based on this model, order batching problem is also analysed. Through numerical experiments, the cost of above decoupling problems is computed under different settings of the speed ratio and the capacity of the picker while he/she is travelling alone. The results indicate how the decoupling of picker and cart leads to cost reduction. Our model shows good performance for orders of small and medium scale and hence has great potential to improve the order picking operation which is executed by decoupling containers and robots/vehicles in modern digital warehouse systems.

关键词： Routing order picking multi-block warehouse mixed-integer linear programming decoupling

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Optimizing Transmission Network Expansion Planning Using Search Space Reduction

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IEEE ACCESS 2025年 13卷 68773-68784页

作者： Meneses, Marco Zamora, Harol Macedo, Leonardo H. Romero, Ruben Sao Paulo State Univ UNESP Sch Engn Dept Elect Engn BR-15385007 Ilha Solteira SP Brazil Sao Paulo State Univ UNESP Sch Engn & Sci Dept Engn BR-19272100 Rosana SP Brazil

Transmission network expansion planning is a critical and complex problem related to the operation and development of electrical power systems. It is typically formulated as a mixed-integer nonlinear programming (MINLP) problem with combinatorial characteristics. Various mathematical models have been proposed to better approximate real-world system behavior, but even the most relaxed formulations remain computationally challenging. This paper introduces a search space reduction strategy to reduce the gap between the optimal solution of the MINLP model and its relaxed counterpart by strategically considering surrogate constraints. This approach enhances computational efficiency, significantly reducing processing time when using an optimization solver. By applying this method, we successfully determined the previously unknown optimal solution for the Brazilian north-northeast system.

关键词： Mathematical models Optimization Search problems Planning Transportation Load flow Complexity theory linear programming Heuristic algorithms Power generation mixed-integer linear programming nonlinear programming optimization of power systems transmission network expansion planning

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Optimal User and Target Scheduling, User-Target Pairing, and Low-Resolution Phase-Only Beamforming for ISAC Systems

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IEEE Transactions on Vehicular Technology 2025年第6期74卷 9888-9893页

作者： Abanto-Leon, Luis F. Maghsudi, Setareh Ruhr University Bochum Bochum44801 Germany

We investigate the joint user and target scheduling, user-target pairing, and low-resolution phase-only beamforming design for integrated sensing and commmunications (ISAC). Scheduling determines which users and targets are served, while pairing specifies which users and targets are grouped into pairs. Additionally, the beamformers are designed using few-bit constant-modulus phase shifts. This resource allocation problem is a nonconvex mixed-integer nonlinear program (MINLP) and challenging to solve. To address it, we propose an exact mixed-integer linear program (MILP) reformulation, which leads to a globally optimal solution. Our results demonstrate the superiority of an optimal joint design compared to heuristic stage-wise approaches, which are highly sensitive to scenario characteristics. © 1967-2012 IEEE.

关键词： mixed-integer linear programming

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A machine learning approach for predicting the best heuristic for a large scaled Capacitated Lotsizing Problem

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OR SPECTRUM 2025年 1-43页

作者： Kaercher, Jens Meyr, Herbert Univ Hohenheim Dept Supply Chain Management D-70593 Stuttgart Germany

For some NP-hard lotsizing problems, many different heuristics exist, but they have different solution qualities and computation times depending on the characteristics of the instance. The computation times of the individual heuristics increase significantly with the problem size, so that testing all available heuristics for large instances requires extensive time. Therefore, it is necessary to develop a method that allows a prediction of the best heuristic for the respective instance without testing all available heuristics. The Capacitated Lotsizing Problem (CLSP) is chosen as the problem to be solved, since it is a fundamental model in the field of lotsizing, well researched and several different heuristics exist for it. The CLSP addresses the problem of determining lotsizes on a production line given limited capacity, product-dependent setup costs, and deterministic, dynamic demand for multiple products. The objective is to minimize setup and inventory holding costs. Two different forecasting methods are presented. One of them is a two-layer neural network called CLSP-Net. It is trained on small CLSP instances, which can be solved very fast with the considered heuristics. Due to the use of a fixed number of wisely chosen features that are relative, relevant, and computationally efficient, and which leverage problem-specific knowledge, CLSP-Net is also capable of predicting the most suitable heuristic for large instances.

关键词： Algorithm selection problem Machine learning Neural network Heuristics Capacitated lotsizing problem mixed-integer linear programming

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An Evolutionary Algorithm for Expensive mixed-integer Black-Box Optimization with Explicit Constraints

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ACM Transactions on Evolutionary Learning and Optimization 2025年第1期5卷 1-16页

作者： Hong, Yuan Arnold, Dirk V. Dalhousie University HalifaxNS Canada

Determining the feasibility of a candidate solution to a constrained black-box optimization problem may be similarly expensive compared to the process of determining its quality, or it may be much cheaper. Constraints that allow obtaining degrees of feasibility or constraint violation without incurring significant computational costs are referred to as explicit. We present an evolutionary algorithm for solving mixed-integer black-box optimization problems where objective function evaluations are expensive but constraints are explicit. We do not assume relaxability of the constraints. The method wraps active-set evolution strategies, an algorithm for solving continuous black-box problems with explicit constraints, in a branching mechanism that allows enforcing integrality constraints. In computer experiments we demonstrate that the algorithm solves a set of mixed-integer problems with significantly fewer objective function evaluations than several algorithms that do not exploit the explicitness of the constraints. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： mixed-integer linear programming

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