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Branch and bound for the fixed-shape unequal area facility layout problem

COMPUTERS & INDUSTRIAL ENGINEERING 2025年 203卷

作者： Ekstedt, Fredrik Salman, Raad Damaschke, Peter Fraunhofer Chalmers Res Ctr Ind Math Chalmers Sci Pk SE-41288 Gothenburg Sweden Chalmers Univ Technol Dept Comp Sci & Engn SE-41296 Gothenburg Sweden Univ Gothenburg SE-41296 Gothenburg Sweden

Models of the Facility Layout Problem (FLP) can be useful for guiding the placement of resources in a factory building or similar. In real-world situations, the placement of the resources is often subject to a set of complex geometrical constraints, consisting of safety distances and work areas that cannot be encroached. This can result in disjoint regions or irregular shapes that must be placed so that a set of overlapping rules are fulfilled. In this paper, we formulate this problem as placing a fixed set of arbitrary polygon unions in a plane such that the overlapping constraints are not violated and the sum of weighted distances between them is minimized. A grid-based approximation and a branch and bound algorithm to solve this variation of the problem are developed. We compare the performance with a linearized QAP formulation solved with state-of-the art MILP solvers. The algorithm shows favorable results, solving problem instances with up to 8 resources to optimality within 48 h.

关键词： Unequal area facility layout planning Branch and bound Combinatorial optimization mixed integer linear programming Quadratic assignment problem

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Multi-Agent Grouping and Routing with Cooperative Tasks

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2025年第3期22卷 163-176页

作者： Choi, Euihyeon Ahn, Jaemyung Korea Adv Inst Sci & Technol KAIST Dept Aerosp Engn 291 Daehak Ro Daejeon 34141 South Korea

This paper introduces a grouping and routing problem of multiple agents for cooperative missions. The introduced problem, referred to as the Vehicle Grouping and Routing Problem with Profits, aims to maximize the total reward obtained by conducting a multi-agent mission (e.g., cooperative reconnaissance) while reducing its makespan by appropriately grouping the agents and determining their routes under operational constraints (e.g., fuel, endurance). A mixed-integer linear programming formulation and a conservative column generation-based solution procedure for the problem are proposed. A case study with homogeneous and heterogeneous agents and numerical experiments involving a cooperative reconnaissance mission with multiple unmanned aerial vehicles demonstrate the validity of the proposed formulation and solution procedure.

关键词： Unmanned Aerial Vehicle mixed integer linear programming Optimization Algorithm Flight Dynamics Autonomous Technology Planetary Science and Exploration Aerospace Engineering

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Analysis of the inter-city shared mobility system based on autonomous electric vehicles

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RENEWABLE ENERGY 2025年 239卷

作者： Wang, Peng Jiang, Han Cui, Yanlei Zhao, Mingming Ren, Yilong Xu, Liang Beihang Univ Hangzhou Innovat Inst Beijing Peoples R China Beihang Univ Sch Transportat Sci & Engn Beijing Peoples R China Beihang Univ State Key Lab Intelligent Transportat Syst Beijing Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian Peoples R China Xidian Univ Hangzhou Inst Technol Hangzhou Peoples R China

While autonomous electric vehicles (AEVs) have been preliminarily implemented in shared travel services from both technical and theoretical perspectives, challenges such as dispersed fleets, limited service quality, and travel safety concerns have confined existing research to intra-city shared mobility, with few studies focusing on inter-city shared mobility for AEVs. With China's metropolitan regions expanding and intercity travel rapidly increasing, examining the use of shared autonomous electric vehicles (SAEVs) for intercity travel is essential for future transportation systems. To address this issue, this study models the inter-city shared mobility problem utilizing mixed integer linear programming. The problem is defined on a directed graph and addressed using a variable neighborhood search algorithm. Numerical experiments are designed based on the actual shared mobility data between Yinchuan and Shizuishan, Ningxia Province, China. From the perspective of the operating platform, the potential influencing factors of the inter-city shared mobility system are analyzed, including passenger travel demand, fleet size, vehicle range, and the number of charging stations. The results demonstrate that increasing temporal and spatial imbalance in passenger travel demand and excessive fleet size will lead to lower total revenue of the operation platform. Conversely, within certain thresholds, increasing the number of charging stations, vehicle range, and fleet size will increase the total revenue. Continuing to increase the number of charging stations and vehicle range has no significant effect on total revenue and service rate but will lead to a waste of basic resources. The study is expected to provide solution for building an inter-city shared mobility system based on SAEVs. By fully understanding the system's limitations and advantages, we aim to provide a reference template for constructing future inter-city shared mobility systems.

关键词： Shared autonomous electric vehicle Inter-city shared mobility system mixed integer linear programming Variable neighborhood search

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Robust Optimization Models for Planning Drone Swarm Missions

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DRONES 2024年第10期8卷 572-572页

作者： Panowicz, Robert Stecz, Wojciech Mil Univ Technol Fac Mech Engn PL-00908 Warsaw Poland Cardinal Stefan Wyszynski Univ Inst Comp Sci Fac Math & Nat Sci PL-01938 Warsaw Poland

This article presents methods of planning unmanned aerial vehicle (UAV) missions in which individual platforms work together during the reconnaissance of objects located within a terrain. The planning problem concerns determining the flight routes of a swarm, where each UAV has the ability to recognize an object using a specific type of sensor. The experiments described in this article were carried out for drone formation;one drone works as a swarm information hub and exchanges information with the ground control station (GCS). Numerical models for mission planning are presented, which take into account the important constraints, simplifying the description of the mission without too much risk of losing the platforms. Several types of objective functions were used to optimize swarm flight paths. The mission models are presented in the form of mixed integer linear programming problems (MILPs). The experiments were carried out on a terrain model built on the basis of graph and network theory. The method of building a network on which the route plan of a drone swarm is determined is precisely presented. Particular attention was paid to the description of ways to minimize the size of the network on which the swarm mission is planned. The presented methods for building a terrain model allow for solving the optimization problem using integer programming tasks.

关键词： swarm unmanned air vehicle UAV mission planning vehicle routing problem VRP mixed integer linear programming MILP

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Comparison of CD and CDC Technologies for Flex Grid DWDM Networks

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IEEE ACCESS 2024年 12卷 116026-116039页

作者： Kozdrowski, Stanislaw Krysztofik, Pawel Sujecki, Slawomir Warsaw Univ Technol Comp Sci Inst PL-00665 Warsaw Poland Wroclaw Univ Sci & Technol Telecommun & Teleinformat Dept PL-50370 Wroclaw Poland Mil Univ Technol Fac Elect PL-00908 Warsaw Poland

The main objective of the paper is to compare CD and CDC nodal architecture technologies for flex grid DWDM optical networks. The methodology adopted consists in optimising a DWDM network for both nodal architectures and comparing the resource utilisation. Several nature-inspired heuristic algorithms, based mainly on an evolutionary algorithm, have been specifically selected to solve the optimisation problem with realistic computational resources. Numerical experiments were carried out for two distinct backbone networks: Polish and American. Using the best of the proposed heuristic methods in terms of the value of the objective function and computation time, CD and CDC technologies were compared. The results obtained show the advantages of CDC technology over CD technology, particularly with respect to utilization of occupied frequency bandwidth of network edges.

关键词： Wavelength division multiplexing Optimization Bandwidth Costs Transponders Routing Mathematical models Metaheuristics Evolutionary computation mixed integer linear programming Optical fiber networks evolutionary algorithm bees algorithm mixed integer linear programming combinatorial optimization new-generation optical network design DWDM CD CDC

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Heuristics Based Optimization for Multidepot Drone Location and Routing Problem to Detect Post-Earthquake Damages

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第1期25卷 850-858页

作者： Aydin, Nezir Yilmaz, Oktay Deveci, Muhammet Lv, Zhihan Yildiz Tech Univ Dept Ind Engn TR-34349 Istanbul Turkiye ERD Informat Technol TR-34873 Istanbul Turkiye Imperial Coll London Royal Sch Mines London SW7 2AZ England Natl Def Univ Turkish Naval Acad Dept Ind Engn TR-34940 Istanbul Turkiye Uppsala Univ Fac Arts Dept Game Design S-62167 Visby Sweden

The aim of this research is to detect the post-disaster damage by drones as soon as possible so that decision makers can assign search and rescue teams effectively and efficiently. The main differences of this research from the others, which use drones in literature, are as: First, the regions are divided into grids and different importance values are assigned according to the number of buildings that are likely to be damaged and are vital for the response stage, such as hospitals, schools, and fire stations. Second, these importance levels are updated based on the day and time, which helps ordering the grids in a more realistic manner. Third, the depots are selected among the pre-determined candidate locations in accordance with the purpose of objective function. Fourth, detection times at grids are considered as uncertain. Fifth, two versions of Ant Colony Optimization (ACO) are developed as alternatives to exact solution tools. Last, sensitivity analyzes are performed by reducing the number of sorties, reducing the number of drones, and comparing day and night importance values for each instance. According to the results, only for very small-scale instances, exact solution tool was able to reach the optimal while both versions of ACO reached to similar results within a very less CPU times. Additionally, these ACO algorithms also found good results for the larger scaled problems. Then the performance of these ACO algorithms and the exact solution method are compared based on the CPU time and solution quality.

关键词： Drones Earthquakes Buildings Routing Mathematical models Path planning Image resolution Post-earthquake damage detection location and routing ant colony optimization mixed integer linear programming drones

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Trade-off between computation time and solution quality for integrated generation and transmission expansion planning with N-1 security criterion

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2025年 164卷

作者： Okamura, Lucas Y. Borges, Carmen L. T. Chicco, Gianfranco PSR Rio De Janeiro Brazil Univ Fed Rio de Janeiro Rio de Janeiro Brazil Politecn Torino Turin Italy

The generation and transmission (G&T) expansion planning of large-scale systems is usually carried out hierarchically due to the high complexity of the problem. However, this hierarchical plan may be more expensive than a fully integrated (co-optimized) G&T plan that, on the other hand, requires high computation time. Therefore, the trade-off between computation time and solution quality is of great importance, especially with the integration of renewable generation. This paper proposes and assesses alternative formulations of the integrated G&T planning problem, also considering the system operation simulation under the N-1 security criterion, seeking to balance solution optimality and computational effort. The assessments are illustrated for the Chilean electrical system. The main outcome is that one of the proposed methods, in which the future cost function is maintained fixed during the generation and transmission optimization and is recalculated only in the final simulation of the system operation, achieves results very close to the fully integrated generation, transmission, and operation optimization method. This method presents a cost reduction of 8 % compared to a hierarchical approach, which represents savings of around 700 million dollars, and 50 % less computation time compared to the fully integrated method. For the same proposed method, the preliminary calculation of an optimal solution without applying the N-1 security constraint as a starting point, followed by re-optimization with active N-1 security constraints, contributes to a 65 % reduction of the computation time without significantly impacting the quality of the solution.

关键词： Power system planning Renewable Generation Security Optimization mixed integer linear programming Stochastic Dual Dynamic programming

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Optimizing battery storage for sustainable energy communities: A multi-scenario analysis

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SUSTAINABLE CITIES AND SOCIETY 2025年 118卷

作者： Guo, Feng Gomes, Luis Ma, Ling Tian, Zhiyong Vale, Zita Pang, Shiyuan Huazhong Univ Sci & Technol Natl Ctr Technol Innovat Digital Construct Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Civil & Hydraul Engn Wuhan 430074 Peoples R China Polytech Porto LASI Intelligent Syst Associate Lab GECAD Res Grp Intelligent Engn & Comp Adv Innovat Porto Portugal Huazhong Univ Sci & Technol Sch Environm Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Environm Sci & Engn Hubei Key Lab Multimedia Pollut Cooperat Control Y Wuhan 430074 Peoples R China Huadian Jinsha River Upstream Hydropower Dev Co Lt Chengdu 610041 Peoples R China

The Energy Community (EC) is expanding worldwide, with Solar Photovoltaic (PV) systems as the primary Renewable Energy Source (RES). However, "solar curtailment" challenges the European Union's 2030 Target of achieving 45 % renewables in final energy consumption. Peer-to-peer (P2P) energy sharing and Battery Energy Storage Systems (BESS) sharing can improve the RES share more effectively, but they face obstacles like high costs and low utilisation rates. This research develops a hybrid model that combines P2P energy sharing with BESS, optimised using mixed integer linear programming (MILP). A new pricing mechanism for P2P transactions and refined Shapley value calculations are introduced. Simulations conducted over 672 h across four seasons and 21,147 scenarios demonstrate that all proposed models effectively increase the renewable energy share. SBES-S and OCBES-S models are the most economical in spring and summer, with EC costs of -13.028 and -55.578. The OCBES-S model is the most cost-effective for autumn and the year, costing 92.998 and 174.101, respectively. Compared to the scenario without BESS and P2P sharing, it reduces annual electricity costs by 16.34 %. This study provides all EC stakeholders with a tool for option comparison and economic analysis, supporting the sustainable development of EC and renewable energy.

关键词： Energy community Battery energy storage systems Peer to peer mixed integer linear programming Renewable energy Sustainable development

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A Policy-Based Meta-Heuristic Algorithm for Energy-Aware Distributed No-Wait Flow-Shop Scheduling in Heterogeneous Factory Systems

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年第1期55卷 620-634页

作者： Zhao, Fuqing Song, Lisi Jiang, Tao Wang, Ling Dong, Chenxin Lanzhou Univ Technol Sch Comp & Commun Lanzhou 730050 Peoples R China Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen 518055 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Qingdao Hengxing Univ Sci & Technol Dept Automot Engn Qingdao 266100 Peoples R China

In the face of environmental deterioration and global climate change, the concept of carbon neutrality and carbon peaking has gained prominence as a means to balance development and environmental preservation worldwide. Energy-aware scheduling is becoming the key scenario for environment conservation in manufacturing. This study focuses on addressing the energy-aware distributed no-wait flow-shop scheduling problem in a heterogeneous factory system (EDNWFSP-HFS) to minimize total energy consumption (TEC) and total tardiness (TTDs). A mixed-integer linear programming (MILP) model is formulated and a policy-based meta-heuristic algorithm (MHA-PG) is specifically designed to solve EDNWFSP-HFS. First, the optimal allocation rules based on random sequence (OAR-RS) are designed to initialize the population. Second, a policy-based method is employed to guide the algorithm toward making a better decision. Third, the energy-saving strategy considering specific knowledge of EDNWFSP-HFS is summarized to further optimize the feasible solution. Extensive simulations are conducted, comparing the performance of MHA-PG against several state-of-the-art algorithms. The results demonstrate that the proposed algorithm outperforms the competing approaches in solving EDNWFSP-HFS, indicating its superior performance and effectiveness.

关键词： Climate change Manufacturing automation Metaheuristics Job shop scheduling Distributed management Energy management Heterogeneous networks Carbon neutral mixed integer linear programming Distributed flow-shop scheduling energy-aware scheduling heterogeneous factory system (HFS) policy-based meta-heuristic

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A Resilience Enhancement Planning Framework Capturing Customers' Participation in Distribution Systems

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IEEE TRANSACTIONS ON SMART GRID 2025年第2期16卷 957-972页

作者： Eshkaftaki, Amin Alavi Latify, Mohammad Amin Fotuhi-Firuzabad, Mahmoud Dehghanian, Payman Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran Sharif Univ Technol Dept Elect Engn Tehran 111554363 Iran George Washington Univ Dept Elect & Comp Engn Washington DC 20052 USA

This paper presents a novel planning framework to enhance the resilience of energy supply to customers in power distribution systems. The framework involves three key stakeholders: the regulator as the governing entity that enforces regulatory mechanisms to oversee the performance of the distribution system operator (DSO);the DSO that reinforces the infrastructure by placing emergency distributed generations and hardening sections, implements necessary operational decisions, and facilitates customers' participation by introducing appropriate incentives;and customers who may (i) gain the desired resilience through investing in self-generation, (ii) rely on the resilience provided by the DSO along with paying the agreed-upon insurance premiums, or (iii) opt for a mix of both approaches. The proposed framework is designed through a four-step process. First, the regulatory mechanisms are established by setting a standard resilience index for the penalty and reward model as well as a revenue cap for the DSO under a revenue-cap regulation using customized optimization problems aimed at optimizing DSO's costs without customers' participation. Next, an integrated resilience enhancement optimization problem that coordinates the strategies of the DSO and customers is formulated as a mixed-integer linear programming model, focusing on the global objective functions of the DSO and customers. Finally, the economic benefits are distributed between the DSO and customers who are justified for investment in self-generation using a suggested method based on Monte-Carlo estimation, in which the Fisher-Yates shuffle technique and a designated optimization problem are employed. Applied to the IEEE 33-bus test system for two case studies, the proposed framework is proven to be effective in enhancing resilience, achieving regulatory objectives, and providing economic benefits for both the DSO and customers, creating a mutually beneficial scenario for all parties involved.

关键词： Resilience Reactive power Planning Costs Investment Indexes linear programming Fault tolerance Substations mixed integer linear programming Customers disruptive events distribution system operator (DSO) mixed-integer linear programming (MILP) regulator resilience

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