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A mixed integer linear programming model for multi-sector planning using speed and heading changes

COMPUTERS & OPERATIONS RESEARCH 2021年 128卷 105174-105174页

作者： Hassan, Mohamed Ossama Saucier, Antoine Yacout, Soumaya Soumis, Francois Ecole Polytech Montreal 2900 Blvd Edouard Montpetit Montreal PQ H3T 1J4 Canada

The Multi-Sector Planning (MSP) concept, adopted in both the SESAR and NextGen projects, promotes the control of aircraft and resolution of conflicts over a medium time horizon to reduce and balance con-troller workload. In the context of MSP, we propose a first formulation of the complexity resolution prob-lem that allows trajectory modifications using both speed and heading changes assuming exact knowledge of aircraft positions. This model is also the first to have the capacity to ensure workload bal-ancing among sectors in a Multi-Sector Area (MSA). The number of crossing conflicts in a sector is used as a measure of controller workload. This problem is formulated as a mixed integer linear programming model that allows obtaining optimal solutions. This model ensures neighbor trajectory recovery and min-imal delays. This model was tested on a set of conflict detection and resolution benchmark test problems with up to 300 simultaneous conflicts. Conflict-free solutions were obtained in less than 1.4 s. The model was also tested on several distinct sets of randomly generated problems with an MSA of four sectors and up to 150 aircraft. The number of crossing conflicts was reduced by more than 99% with a computation time smaller than four seconds. It was found that it is beneficial to allow the use of both speed and head-ing changes in high traffic situations. It was also found that considering workload balancing allows the minimization of the total workload in the MSA while preventing overloading some sectors. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Multi-sector planning Air traffic control Conflict detection and resolution Workload balancing mixed integer linear programming

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Energetic and economic optimization of the yearly performance of three different solar assisted heat pump systems using a mixed integer linear programming algorithm

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ENERGY CONVERSION AND MANAGEMENT 2020年第0期206卷 112446-000页

作者： Simonetti, Riccardo Moretti, Luca Molinaroli, Luca Manzolini, Giampaolo Politecn Milan Dipartimento Energia Via Lambruschini 4 I-20156 Milan Italy

This paper presents a yearly energetic and economic assessment of three different solar assisted heat pump concepts integrated with electrical and thermal storages and applied to a single-family house. The three heat pump-based systems are (i) a conventional air-to-water heat pump plus photovoltaic solar modules, (ii) a water-to-water heat pump coupled to hybrid photovoltaic-thermal solar modules and (iii) a dual source heat pump integrated with hybrid photovoltaic-thermal solar modules. The energetic and economic analysis is performed using physically-based models of each component for different numbers of solar modules and sizes of the electric storage. The maximum economic saving of these highly integrated systems is determined through an optimization algorithm based on the mixed integer linear programming technique. The results show that the dual source heat pump system with the largest battery size is the system that achieves the highest energetic performance, i.e. 77% primary energy saving with respect to traditional boiler-based system, whereas the lowest operating cost and the highest economic saving are obtained using the conventional air-to-water heat pump without any electric storage since it achieves 31% economic saving compared with the baseline system.

关键词： Economic analysis Energetic analysis mixed integer linear programming Hybrid photovoltaic/thermal collectors Solar assisted heat pump

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Makespan optimization using Timed Petri Nets and mixed integer linear programming Problem

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IFAC-PapersOnLine 2020年第4期53卷 129-135页

作者： E. Di Marino R. Su F. Basile University of Salerno DIEM Italy Nanyang Technological University School of Electrical & Electronic Engineering Singapore

In this paper, a method for generating a mixed integer linear programming problem from deterministic timed Petri nets to optimize the makespan of manufacturing systems is proposed. After exposing several challenges involved in such a model transformation, a novel method is exploited to overcome them. The adopted solution may create a synergy between the highly expressive timed Petri net modelling framework and the computational attractive mathematical programming tool set.

关键词： Discrete Event Systems Timed Petri Nets mixed integer linear programming

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Dynamic Fleet Configuration Model for Optimizing Earthmoving Operations Using mixed integer linear programming

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JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT 2024年第11期150卷 04024152-04024152页

作者： Khallaf, Zaid Alshibani, Adel Alsawafy, Omar Mohammed, Awsan Bubshait, Abdulaziz King Fahd Univ Petr & Minerals Appl Res Ctr Metrol Stand & Testing Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Dept Architectural Engn & Construct Management Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Interdisciplinary Res Ctr Construct & Bldg Mat Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Dept Ind & Syst Engn Dhahran 31261 Saudi Arabia

Practitioners in construction management primarily focus on two key indicators of project success: total cost and completion time. Heavy equipment and machinery play pivotal role in determining these measures, representing significant cost elements in various heavy construction projects such as road construction. Consequently, there is a pressing need for an efficient approach to determining the optimal scheduling of these heavy resources to minimize costs and shorten completion times. This paper proposes an innovative approach to address this challenge by introducing a mixed integer linear programming (MILP) model. The aim is to identify the optimal configuration for heavy equipment in earthmoving operations. The dynamic nature of the configuration process is adopted, enabling daily updates to the schedule based on the contractor's available resources. Moreover, environmental considerations are integrated into the decision-making process, ensuring a comprehensive approach to project optimization. To demonstrate the superiority of the developed model, three case projects from the literature have been solved. The proposed model led to a significant improvement in project cost, with an average enhancement of 25%, and in completion time, with an average improvement of 50% compared with the literature case studies. This paper presents a novel MILP model designed to optimize earthmoving operations, focusing on dynamic fleet configurations and emission costs. Unlike existing models, this approach provides daily fleet setups for multiple cut and fill sites, considering the contractor's available resources. It calculates optimal soil quantities to be moved, monitors soil levels at sites, and estimates daily trips between them. In the realm of project bidding and management, this model offers valuable insights and practical applications. It empowers project managers with a robust tool for optimizing fleet configurations during bid preparation, enabling contractors to determi

关键词： Dynamic fleet configuration Earthmoving optimization Construction management Fleet management mixed integer linear programming

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Disassembly line balancing with sequencing decisions: A mixed integer linear programming model and extensions

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JOURNAL OF CLEANER PRODUCTION 2019年 238卷 117826-000页

作者： Edis, Emrah B. Ilgin, Mehmet Ali Edis, Rahime Sancar Manisa Celal Bayar Univ Dept Ind Engn Sehit Prof Dr Ilhan Varank Kampusu TR-45140 Yunusemre Manisa Turkey

Due to the acceleration of technological developments and shortening of product life cycles, product recovery has gained great importance in recent years. Disassembly line balancing (DLB) problem is one of the most important problems encountered during disassembly operations in product recovery. In this study, a single model and complete DLB problem with balancing issues, hazardousness of parts, demand quantities and direction changes is considered. Majority of DLB studies in the literature solve this problem using heuristics or metaheuristics which do not guarantee the optimality. Although a few studies present mathematical formulations for some variants of this problem, they prefer to solve the problem by using heuristics or metaheuristics due to the non-linear structure and combinatorial nature of the problem. In this study, a generic mixed integer linear programming (MILP) model is developed for the investigated problem and its performance is tested through a series of benchmark instances. The computational results demonstrate that the proposed MILP model is able to solve test instances with up to 30 tasks. Hence, it can effectively be utilized to evaluate the optimality performance of DLB approaches. Moreover, several extensions on the MILP model regarding to line balancing, hazardousness and demand of parts and direction changes are proposed and their effects are analyzed through computational studies. (c) 2019 Elsevier Ltd. All rights reserved.

关键词： Disassembly line balancing Sequencing mixed integer linear programming

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Modeling Favorable Locations for Biogas Plants that Generate Electricity from Dairy and Beef Cattle Manure through mixed integer linear programming

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BIORESOURCES 2024年第3期19卷 4517-4530页

作者： Yilmaz, Halil Ibrahim Gonbe, Yalcin Isparta Univ Appl Sci Dept Agr Struct & Irrigat TR-32260 Isparta Turkiye

mixed integer linear programming (MILP) is known as a type of programming that can combine continuous variables, integer variables, and (0-1) variables in the same algorithm and generate fiffing results for the data. Using this technique, it is possible to model and solve complex problems in many different fields such as economics, biology, engineering, etc. In the present study, a regional planning model was developed using MILP technique for the conversion of manure from dairy and beef cattle into biogas and electrical energy. For this regional planning study, considering the locations of future facilities, data on dairy and beef cattle in the Isparta province of TOrkiye were used. According to the model written and solution outputs, to utilize all manure obtained from dairy and beef cattles in Isparta, 5 biogas plants with a total manure processing capacity of approximately 522,000 tons should be built in different districts. It is possible to produce a total of approximately 21,000,000 m 3 of biogas and 38,500 MW of electricity per year in these biogas plants. This electrical energy obtained can meet 3.83% of the annual electricity consumption of Isparta province.

关键词： Optimization Biogas mixed integer linear programming Manure management Planning model

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Portfolio optimization in district heating: Merit order or mixed integer linear programming?

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ENERGY 2023年 265卷

作者： Gonzalez-Salazar, Miguel Klossek, Julia Dubucq, Pascal Punde, Thomas Vattenfall Warme Berlin AG Berlin Germany

Long-term portfolio optimization is commonly used to find the most cost-effective design and operation of a district heating system, subject to technical, financial, and environmental restrictions. Optimizing a district heating system is not trivial and demands high accuracy and high computational speed. However, existing methods addressing this problem offer one or the other but not both at the same time. The state-of-the-art method for portfolio optimization is mixed integer linear programming (MILP), which is extensively used in industry and academia but can be computing and resource-intensive for large portfolio models. This limitation has motivated the development of various options to reduce the computation time while maintaining the ac-curacy to a large extent. An alternative method to MILP is the merit order (MO) method, which has been used especially for power generation applications due to its simplicity and faster computation but somewhat reduced accuracy. The aim of this paper is to investigate the potential advantages and disadvantages of MO models compared to MILP models in the context of optimizing the portfolio of assets supplying a district heating network. As a study case, we analyze a large portion of the district heating network in Berlin. Four MO model variants with different levels of complexity are proposed and compared to a reference MILP model. Results suggest that MO models variants including heat storage and describing CHP plants with significant detail have the potential to reduce calculation time by nearly three orders of magnitude compared to the reference MILP model, without significantly sacrificing accuracy. In fact, differences in heat generation and net present value (NPV) between the most accurate MO model and the reference MILP model account for +/- 4% and-6%, respectively. Moreover, results show that combining MO and MILP models is advantageous and offers high computational speed and at the same time high accuracy, especially wh

关键词： District heating Portfolio optimization mixed integer linear programming Marginal costs Merit order

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A design and analysis of computer experiments based mixed integer linear programming approach for optimizing a system of electric vehicle charging stations

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 245卷

作者： Chawal, Ukesh Rosenberger, Jay Chen, Victoria C. P. Lee, Wei J. Wijemanne, Mewan Punugu, Raghavendra K. Kulvanitchaiyanunt, Asama Univ Texas Arlington Dept Ind Mfg & Syst Engn Arlington TX 76019 USA Boeing Co Boeing Res & Technol Integrated Vehicle Syst 2750 Regent Blvd Dallas TX 75261 USA Univ Texas Arlington Dept Elect Engn Arlington TX 76019 USA

This paper formulates a mixed integer linear programming (MILP) model to optimize a system of electric vehicle (EV) charging stations. Our methodology introduces a two-stage framework that integrates the first-stage system design problem with a second-stage control problem of the EV charging stations and develops a design and analysis of computer experiments (DACE) based system design optimization solution method. Our DACE approach generates a metamodel to predict revenue from the control problem using multivariate adaptive regression splines (MARS), fit over a binned Latin hypercube (LH) experimental design. Comparing the DACE based approach to using a commercial solver on the MILP, it yields near optimal solutions, provides interpretable profit functions, and significantly reduces computational time for practical application.

关键词： Electric Vehicle Charging Stations Latin Hypercube Sampling mixed integer linear programming Multivariate Adaptive Regression -Splines Design and Analysis of Computer-Experiments

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A mixed integer linear programming model for minimum backbone grid

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FRONTIERS IN ENERGY RESEARCH 2023年 10卷

作者： Mei, Wenwen Sun, Zhiyuan He, Yuanjian Liu, Mosi Gong, Xianfu Li, Peijie Guangxi Univ Inst Power Syst Optimizat Sch Elect Engn Nanning Peoples R China Guangxi Power Grid Co Ltd Elect Power Res Inst Nanning Peoples R China Power China Engn Co Ltd Chengdu Elect Power Invest & Design Inst Chengdu Peoples R China Guangdong Power Grid Co Ltd Planning & Res Ctr Guangzhou Peoples R China

Developing a minimum backbone grid in the power system planning is beneficial to improve the power system's resilience. To obtain a minimum backbone grid, a mixed integer linear programming (MILP) model with network connectivity constraints for a minimum backbone grid is proposed. In the model, some constraints are presented to consider the practical application requirements. Especially, to avoid islands in the minimum backbone grid, a set of linear constraints based on single-commodity flow formulations is proposed to ensure connectivity of the backbone grid. The simulations on the IEEE-39 bus system and the French 1888 bus system show that the proposed model can be solved with higher computational efficiency in only about 30 min for such a large system and the minimum backbone grid has a small scale only 52% of the original grid. Compared with the improved fireworks method, the minimum backbone grid from the proposed method has fewer lines and generators.

关键词： minimum backbone grid mixed integer linear programming connectivity constraints single-commodity flow resilience

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Stochastic optimization of comfort-centered model of electrical water heater using mixed integer linear programming

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2020年 42卷

作者： Najafi, Foad Fripp, Matthias Univ Hawaii Manoa Dept Elect Engn 2540 Dole St Honolulu HI 96822 USA

This paper introduces a new strategy for controlling electric water heaters (EWH) using mixed-integer linear programming (MILP). It has two major contributions: 1) To balance between cost savings and the discomfort (cold water) that Demand Response (DR) could bring, the discomfort is modeled as undelivered energy in the objective of the problem rather than a thermal constraint. This improves both sides of the cost-saving Vs. User-comfort trade-ff. 2) in EWH control, many previous works only rely on electricity prices for scheduling. However, this work is among the very few works that also consider consumption for scheduling. Further, by treating the hot water withdrawal pattern as a random variable, the algorithm finds the best setpoints for EWH via stochastic optimization over a range of possible hot water withdrawal patterns, rather than requiring perfect foresight of withdrawal. The result of these changes is an algorithm that can let the temperature fall below minimum when probability of energy usage is low without affecting user comfort while other methods always keep the temperature above minimum. The effectiveness of this approach on improving both sides of the cost Vs. discomfort trade-off and the effectiveness of stochastic approach is confirmed by comparison with two other methods.

关键词： Thermal comfort Demand response Electric water heater scheduling Stochastic optimization mixed integer linear programming Smart grids

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