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Optimization of garbage collection routes for evidence-based policy-making

ARTIFICIAL LIFE AND ROBOTICS 2025年第1期30卷 156-164页

作者： Kaho, Tomoki Sakakibara, Kazutoshi Arimura, Mikiharu Watanabe, Shinya Muroran Inst Technol Muroran Hokkaido Japan Toyama Prefectural Univ Imizu Toyama Japan

This study models garbage collection in a local city in Hokkaido, Japan, driven by the increasing burden of collection costs despite a declining population. A unique problem in this city is the large number of garbage stations, which exacerbates the collection burden. We examine the impact of waste volume fluctuations and the number and layout of garbage stations on collection routes and costs to find solutions to this issue. This research aims to develop cost-effective and feasible garbage collection strategies to support evidence-based policymaking. We formulated a garbage collection challenge using mixed integer linear programming to minimize travel distances and operational burdens within vehicle capacity constraints. Numerical simulations reveal significant findings: (i) optimized routes reduce total travel distance by similar to\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}25% compared to existing routes, (ii) increased waste volumes lead to non-linear increases in route lengths, and (iii) the aggregation strength of garbage stations significantly impacts route efficiency and the number of required stations. Conclusively, this study provides empirical evidence to guide policymakers in optimizing garbage collection systems, ensuring effective resource utilization and maintaining service quality.

关键词： Route optimization Evidence-based policy-making mixed integer linear programming Branch-and-cut method Garbage collection Waste management

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Integrated Hybrid Renewable Energy System Optimization for Sustainable Agricultural Operations

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PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY 2025年第1期9卷 367-386页

作者： Mohammed, Awsan King Fahd Univ Petr & Minerals Architectural Engn & Construct Management Dept Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Interdisciplinary Res Ctr Smart Mobil & Logist Dhahran 31261 Saudi Arabia

The reliance on traditional fossil fuels in agriculture leads to rising energy costs, environmental degradation, and vulnerability to climate change. Transitioning to renewable energy systems can provide cost savings, enhance sustainability, and improve resilience against energy supply disruptions. Embracing these technologies is essential for promoting efficient agricultural practices. Consequently, this paper proposes a mixed-integer linear programming model (MILP) for optimizing the configuration of hybrid photovoltaic, wind, and hydrogen renewable energy systems, with the objective of reducing the overall life cycle costs of greenhouse farms in Saudi Arabia. The model calculates the capacities of individual components, including photovoltaic (PV) modules, wind turbines, hydrogen storage tanks, fuel cells, and electrolyzers. The proposed model is solved using the General Algebraic Modeling System (GAMS) software. The results show that for a farm consisting of 20 greenhouses, employee accommodations, and a water treatment facility, the optimal system includes 552 PV panels (with a capacity of 150 W), 7 wind turbines (with a capacity of 10 kW), 6 fuel cells, 9 electrolyzers, and 2144 hydrogen tanks for storage (with a nominal capacity of 0.3 kWh). The annual energy cost is estimated at $100,527.84, with a levelized cost of energy (LCOE) of $0.056/kWh. The system also yields a reduction in CO2 emissions of 903.631 tons per year, highlighting the potential of hydrogen as a feasible energy storage solution to mitigate fluctuations in renewable energy output. The findings demonstrate the viability of renewable energy in agricultural applications and emphasize the importance of hybrid configurations for energy efficiency. Future studies will explore the integration of other renewable resources and advanced optimization methods to further enhance cost savings and system performance.

关键词： Agricultural operations Hybrid renewable energy system mixed integer linear programming Optimization Hydrogen

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Optimal discrete pipe sizing for tree-shaped CO2 networks

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OR SPECTRUM 2024年第4期46卷 1163-1187页

作者： Pedersen, Jaap Le, Thi Thai Koch, Thorsten Zittel, Janina Zuse Inst Berlin Berlin Germany Tech Univ Berlin Berlin Germany

For industries like the cement industry, switching to a carbon-neutral production process is impossible. They must rely on carbon capture, utilization and storage (CCUS) technologies to reduce their production processes' inevitable carbon dioxide (CO2) emissions. For transporting continuously large amounts of CO2, utilizing a pipeline network is the most effective solution;however, building such a network is expensive. Therefore minimizing the cost of the pipelines to be built is extremely important to make the operation financially feasible. In this context, we investigate the problem of finding optimal pipeline diameters from a discrete set of diameters for a tree-shaped network transporting captured CO2 from multiple sources to a single sink. The general problem of optimizing arc capacities in potential-based fluid networks is already a challenging mixed-integer nonlinear optimization problem. The problem becomes even more complex when adding the highly sensitive nonlinear behavior of CO2 regarding temperature and pressure changes. We propose an iterative algorithm splitting the problem into two parts: (a) the pipe-sizing problem under a fixed supply scenario and temperature distribution and (b) the thermophysical modeling, including mixing effects, the Joule-Thomson effect, and heat exchange with the surrounding environment. We demonstrate the effectiveness of our approach by applying our algorithm to a real-world network planning problem for a CO2 network in Western Germany. Further, we show the robustness of the algorithm by solving a large artificially created set of network instances.

关键词： Carbon capture and storage CO(2 )pipeline transport Network design Discrete pipeline sizing mixed integer linear programming Thermophysical modeling

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A MILP Optimization Model for Sizing a Hybrid Concentrated Solar Power-Wind System Considering Energy Allocation

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PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY 2024年第5期8卷 1527-1544页

作者： Ghaithan, Ahmed M. Al Hanbali, Ahmad Mohammed, Awsan Abdel-Aal, Mohammad King Fahd Univ Petr & Minerals Architectural Engn & Construct Management Dept Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Ind & Syst Engn Dept Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Res Ctr Smart Mobil & Logist Dhahran 31261 Saudi Arabia

This paper develops a mixed integer linear programming model for the optimal sizing of a hybrid concentrated solar power-wind system. The proposed model simultaneously allocates the energy generation among the system's components and determines the optimal system configuration. The hybrid system is compared with a pure wind system with batteries and a pure concentrated solar power system with thermal energy storage. The obtained results of the three systems are validated by benchmarking against other systems in the literature to highlight the novelty of the proposed model. A case study in a residential area at King Fahd University of Petroleum and Minerals, Saudi Arabia, demonstrates the utility and practicality of the developed model. The optimal configuration of the hybrid system comprises a solar field area of 26,257 square meters and 51 wind turbines with an energy cost of 0.172 $/kWh. However, the pure wind system with battery system and the pure concentrated solar power system with thermal energy storage have a cost of energy of 0.534 $/kWh and 0.194 $/kWh, respectively. Additionally, the hybrid system shows significant environmental benefits by reducing CO2 emissions by more than 90% compared to the grid.

关键词： Concentrating solar power Wind turbine energy mixed integer linear programming Optimization Thermal energy storage Battery energy storage

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Bi-level stochastic optimization model of smart distribution grids considering the transmission network to reduce vulnerability

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ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS 2025年第2期16卷 851-884页

作者： Ghanaei, Niki Moghaddam, Mahmoud Samiei Alibeaki, Esmaeil Salehi, Nasrin Davarzani, Reza Islamic Azad Univ Dept Elect Engn Shahrood Branch Shahrood Iran Islamic Azad Univ Dept Elect Engn Damghan Branch Damghan Iran Islamic Azad Univ Dept Basic Sci Shahrood Branch Shahrood Iran

This paper presents a novel optimization framework for integrating transmission and distribution networks. The proposed framework consists of a bi-level optimization model, which comprises an upper-level problem and a lower-level problem. The upper-level problem addresses unit commitment (UC) in the transmission network, aiming to minimize operating costs and load shedding. It is formulated as a mixed-integer linear programming model (MILP). Meanwhile, the lower-level problem focuses on the optimal operation of the distribution network, considering both renewable and non-renewable resources, as well as electric vehicle charging stations (EVCS). This problem is formulated as a linear model with the objectives of reducing power purchase costs from the transmission network and maximizing the utilization of renewable energy and EVCS charging power. The literature review highlights three main research gaps. Firstly, it is crucial to develop a convex model that ensures globally optimal solutions. Secondly, considering the problem-solving time, it is important to devise a method that can achieve globally optimal solutions in the shortest possible time, accounting for the dimensions, number of variables, and parameters involved in coordinating the transmission and distribution networks. Lastly, there is a need to develop a modeling approach that allows the integration of any number of distribution networks with the transmission network. To address these research gaps, we propose a solution methodology that involves rewriting the optimization problems using reformulation and decomposition methods. This approach enables the modeling of globally optimal solutions while ensuring faster solution times and the ability to incorporate numerous distribution networks into the transmission network. We validate the proposed model and methodology using various networks, and the results demonstrate the efficiency of our approach in coordinating the operation of transmission and smart dis

关键词： Coordination of transmission and distribution network Bi-level stochastic optimization Renewable energy mixed integer linear programming

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Optimizing vehicle route, schedule, and platoon formation considering time-dependent traffic congestion

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 192卷

作者： Choi, Jaeseok Do Chung, Byung Yonsei Univ Dept Ind Engn 50 Yonsei Ro Seoul 03722 South Korea

Vehicle platooning, a strategy where vehicles drive in close formations, has emerged as a promising approach to reduce fuel consumption. This study presents a comprehensive model of the time-dependent vehicle platooning problem, which synchronously considers routing, scheduling, and platoon formation to minimize total fuel costs in a network affected by time-dependent traffic congestion. We first propose a mixed integer linear programming model to address this problem. To solve the problem, we develop two solution methods: a tabu search method and a platoon clustering algorithm. Through numerical experiments, we demonstrate the effectiveness of our mathematical model and the efficiency of the proposed algorithms. Our findings provide insights into the operational aspects of platooning and reveal that time-dependent traffic congestion can reduce the fuel-saving effects of platooning. This study underscores the importance of considering time-dependent traffic congestion in route planning and scheduling to ensure the effectiveness of vehicle platooning.

关键词： Vehicle platooning Time -dependent traffic congestion mixed integer linear programming Tabu search Platoon clustering

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Regional Constellation Reconfiguration Problem: integer linear programming Formulation and Lagrangian Heuristic Method

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JOURNAL OF SPACECRAFT AND ROCKETS 2023年第6期60卷 1828-1845页

作者： Lee, Hang Woon Ho, Koki West Virginia Univ Dept Mech & Aerosp Engn Morgantown WV 26506 USA Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta GA 30332 USA

A group of satellites, with either homogeneous or heterogeneous orbital characteristics and/or hardware specifications, can undertake a reconfiguration process due to variations in operations pertaining to Earth observation missions. This paper investigates the problem of optimizing a satellite constellation reconfiguration process against two competing mission objectives: 1) the maximization of the total coverage reward, and 2) the minimization of the total cost of the transfer. The decision variables for the reconfiguration process include the design of the new configuration and the assignment of satellites from one configuration to another. We present a novel biobjective integer linear programming formulation that combines constellation design and transfer problems. The formulation lends itself to the use of generic mixed-integer linear programming (MILP) methods such as the branch-and-bound algorithm for the computation of provably optimal solutions;however, these approaches become computationally prohibitive even for moderately sized instances. In response to this challenge, this paper proposes a Lagrangian relaxation-based heuristic method that leverages the assignment problem structure embedded in the problem. The results from the computational experiments attest to the near-optimality of the Lagrangian heuristic solutions and a significant improvement in the computational runtime as compared to a commercial MILP solver.

关键词： Satellite Constellations Earth Observation mixed integer linear programming Orbital Maneuvers Computing and Informatics Reconfiguration Lagrangian Relaxation

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Virtual Target Selection for a Multiple-Pursuer-Multiple-Evader Scenario

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2025年第5期22卷 391-400页

作者： Weintraub, Isaac E. Von Moll, Alexander Casbeer, David W. Manyam, Satyanarayana G. Air Force Res Lab Control Sci Ctr Wright Patterson AFB OH 45433 USA InfoSciTex Corp 4027 Col Glenn Hwy Dayton OH 45431 USA

This paper considers an N-pursuer-M-evader scenario involving L virtual targets. The virtual targets serve as an intermediary target for the pursuers, allowing the pursuers to delay their final assignment to the evaders. However, upon reaching the virtual target, the pursuers must decide which evader to capture. It is assumed that there are more pursuers than evaders and that the pursuers are faster than the evaders. The objective is two-part: first, assign each pursuer to a virtual target and evader such that the pursuer team's energy is minimized, and, second, choose the virtual targets' locations for this minimization problem. The approach taken is to consider the Apollonius geometry between each pursuer's virtual target location and each evader. Using the constructed Apollonius circles, the pursuer's travel distance and maneuver at a virtual target are obtained. These metrics serve as a gauge for the total energy required to capture a particular evader and are used to solve the joint virtual target selection and pursuer-evader assignment problem. This paper provides a mathematical definition of this problem, the solution approach taken, and an example. Following the example, a Monte Carlo analysis is performed, demonstrating the efficacy of the algorithm and its suitability for real-time applications.

关键词： mixed integer linear programming Optimal Control Theory Optimization Algorithm Weapon Target Assignment Monte Carlo Analysis Guidance, Navigation, and Control Systems Missile Defense

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Compact Models to Solve the Precedence-Constrained Minimum-Cost Arborescence Problem with Waiting Times

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ALGORITHMS 2024年第1期17卷 12页

作者： Dell'Amico, Mauro Jamal, Jafar Montemanni, Roberto Univ Modena & Reggio Emilia Dept Sci & Methods Engn Via Amendola 2 I-42122 Reggio Emilia RE Italy Univ Modena & Reggio Emilia Interdept Ctr En&Tech Capannone 19 TecnopoloPiazza Europa 1 I-42122 Reggio Emilia RE Italy

The minimum-cost arborescence problem is a well-studied problem. Polynomial-time algorithms for solving it exist. Recently, a new variation of the problem called the Precedence-Constrained Minimum-Cost Arborescence Problem with Waiting Times was presented and proven to be NP-hard. In this work, we propose new polynomial-size models for the problem that are considerably smaller in size compared to those previously proposed. We experimentally evaluate and compare each new model in terms of computation time and quality of the solutions. Several improvements to the best-known upper and lower bounds of optimal solution costs emerge from the study.

关键词： arborescences precedence constraints mixed integer linear programming constraint programming

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Stochastic optimal scheduling of wind power and pumped-storage hydropower complementary systems with multiple uncertainties

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JOURNAL OF ENERGY STORAGE 2024年 78卷

作者： Lu, Na Su, Chengguo Guo, Chaoyu Wang, Peilin Wu, Huijun Sui, Quan Zhengzhou Univ Coll Water Conservancy & Transportat Zhengzhou 450001 Peoples R China Zhengzhou Univ Yellow River Lab Zhengzhou 450001 Peoples R China Design & Res Co Ltd China Water Resources Bei Fang Invest Tianjin 300222 Peoples R China China Southern Power Grid Co LTD Power Dispatching & Control Ctr Guangzhou Peoples R China Zhengzhou Univ Sch Elect & Informat Engn Zhengzhou 450001 Peoples R China

The joint operation of wind farms (WFs) and pumped-storage hydropower plants (PSHPs) is an effective way to smooth out the random fluctuations of wind power and improve its consumption rate. In this paper, a novel method to describe the multiple uncertainties of wind power outputs is proposed. A WFs-PSHP joint optimal scheduling model based on chance-constrained programming is then developed. The optimization model aims to maximize the total generation profit of the WFs-PSHP complementary system, and comprehensively considers the hydraulic constraints, unit operation constraints and system power balance constraint of the PSHP. To improve the model solving efficiency, this study converts the previous model with high-dimensional, nonconvex, nonlinear and stochastic characteristics to the deterministic mixed integer linear programming (MILP) one. The optimization results demonstrate that the PSHP not only compensates for the fluctuations in wind power output, but also increases the total generation profit of this complementary system to 966.48 x 104 CNY, which is 17.56 % higher than that of independent operation.

关键词： Chance -constrained programming WFs-PSHP complementary systems Multiple uncertainties of wind power output mixed integer linear programming

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