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An integrated model for airport runway assignment and aircraft trajectory optimisation

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2024年 160卷

作者： Barea, Adrian de Celis, Raul Cadarso, Luis Rey Juan Carlos Univ Aerosp Syst & Transport Res Grp Camino Molino 5 Fuenlabrada 28942 Madrid Spain

Air traffic management of terminal manoeuvring area involves high complexity as air traffic converges to airports. In addition, air traffic is currently experiencing a remarkable growth despite the COVID19 pandemic effects. This trend, which is expected to continue in the mid and near future, motivates the development of methodologies that improve the efficiency and automatisation of air traffic management processes to efficiently prevent bottlenecks in current airports instead of expanding or building new facilities, which usually implies higher costs. Specifically, runway assignment is of capital importance for the correct exploitation of current airports capacity. In this paper, a mixed integer non -linear model is presented which deals with aircraft approach and landing operations. It integrates decisions regarding runway assignment and trajectory optimisation. Since this problem is difficult to be solved, a Benders decomposition is proposed. The master model deals with runway assignment, resulting in a mixed integer linear programming model. The submodel deals with the trajectory determination problem, resulting in a nonlinear programming model that minimises a combination of fuel consumption and aircraft delay while complying with operational constraints. In addition, a rolling horizon approach is employed for real -size case studies, which systematically optimises operations within 30-min intervals. Computational results on real-world problem instances of Madrid-Barajas airport are reported. Our solutions are found to be tractable and robust in the face of data variations.

关键词： Trajectory optimisation Runway assignment Airport operations mixed integer non-linear programming Benders decomposition

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Multi-period multi-echelon inventory transportation problem considering stakeholders behavioural tendencies

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2020年 225卷 107566-107566页

作者： De, Arijit Mogale, D. G. Zhang, Mengdi Pratap, Saurabh Kumar, Sri Krishna Huang, George Q. Newcastle Univ Business Sch Newcastle Upon Tyne NE1 4SE NE England Indian Inst Technol Dept Ind & Syst Engn Kharagpur 721302 W Bengal India Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing 210003 Peoples R China Indian Inst Informat Technol Design & Mfg Dept Mech Engn Jabalpur India Univ Hong Kong Dept Ind & Mfg Syst Engn HKU ZIRI Lab Phys Internet Hong Kong Peoples R China

An inventory transportation problem of manufacturing organization focusing on several stakeholders such as manufacturers, distributors, wholesalers, retailers and customers is addressed in this paper. The research study considered multi-echelon, multi-product, multi-modal and multi-period scenario. The mathematical model in the form of mixed integer non-linear programming is formulated to minimize the total cost associated with transportation, inventory holding and operational activities. A mathematical formulation based heuristic approach, which comprises of four algorithms, is proposed for solving purpose. The proposed heuristic approach considers the behavioural tendencies of stakeholders pertaining to the selection of shipment routes, transportation mode choice decisions and amount of products to be shipped. Fifteen practical problem instances are solved by using the developed heuristic approach while considering the behavioural aspects of stakeholders. Insights obtained from results will be beneficial for manufacturing organizations in making informed decisions related to transportation planning considering stakeholder's behavioural tendencies.

关键词： Inventory Transportation Supply chain network Manufacturing mixed integer non-linear programming Heuristic

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Strategic design of competing supply chain networks for inelastic demand

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2011年第10期62卷 1784-1795页

作者： Rezapour, S. Farahani, R. Zanjirani Drezner, T. Amirkabir Univ Technol Dept Ind Engn Tehran 15914 Iran Calif State Univ Fullerton Fullerton CA 92634 USA

A model for designing the network of a new entrant supply chain under inelastic demand and in the presence of pre-existing competing chains is proposed. These supply chains provide an identical product for a market area. The model considers the location of distribution centres and retail outlets on a discrete set of potential locations. The assumptions of the model are: (1) static competition between the new and pre-existing chains and (2) a probabilistic customer behaviour based on an attraction function depending on both the location and the quality of the retailers. This model also incorporates the impact of the facilities' location decisions on the operational inventory and shipment decisions. The resulting model is formulated as a mixed integer non-linear programme (MINLP). To solve the MINLP it is transformed to a linear one. We illustrate the model, discuss the results of a real-world case, and investigate the effectiveness of the proposed algorithm using randomly generated examples. Journal of the Operational Research Society (2011) 62, 1784-1795. doi:10.1057/jors.2010.146 Published online 17 November 2010

关键词： supply chains network design mixed integer non-linear programming static competition

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Exact global optimization of frame structures for additive manufacturing

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2022年第3期65卷 97-97页

作者： Toragay, Oguz Silva, Daniel F. Vinel, Alexander Shamsaei, Nima Auburn Univ Ind & Syst Engn Dept Auburn AL 36849 USA Auburn Univ Mech Engn Dept Auburn AL 36849 USA

We consider the problem of designing lightweight load-bearing frame structures with additive manufacturability constraints. Specifically, we focus on mathematical programming approaches to finding exact globally optimal solutions, given a pre-specified discrete ground structure and continuous design element dimensions. We take advantage of stiffness matrix decomposition techniques and expand on some of the existing modeling approaches, including exact mixed-integer nonlinear programming and its mixed-integer linear programming restrictions. We propose a (non-convex) quadratic formulation using semi-continuous variables, motivated by recent progress in state-of-the-art quadratic solvers, and demonstrate how some additive-specific restrictions can be incorporated into mathematical optimization. While we show with numerical experiments that the proposed methods significantly reduce the required solution time for finding global optima compared to other formulations, we also observe that even with these new techniques and advanced computational resources, discrete modeling of frame structures remains a tremendously challenging problem.

关键词： Discrete topology optimization Additive manufacturing Frame structures mixed integer non-linear programming mixed integer quadratically constrained programming mixed integer linear programming

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Optimal Access Point Power Management for Green IEEE 802.11 Networks

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SENSORS 2021年第6期21卷 2076-2076页

作者： Garroppo, Rosario G. Nencioni, Gianfranco Tavanti, Luca Gendron, Bernard Scutella, Maria Grazia Univ Pisa Dept Ingn Informaz I-56122 Pisa Italy Univ Stavanger Dept Elect Engn & Comp Sci N-4021 Stavanger Norway CUBIT Consortium Ubiquitous Technol I-56021 Cascina Italy Univ Montreal CIRRELT Montreal PQ H3T 1N8 Canada Univ Montreal DIRO Montreal PQ H3T 1N8 Canada Univ Pisa Dept Informat I-56127 Pisa Italy

In this paper, we present an approach and an algorithm aimed at minimising the energy consumption of enterprise Wireless Local Area Networks (WLANs) during periods of low user activity. We act on two network management aspects: powering off some Access Points (APs), and choosing the level of transmission power of each AP. An efficient technique to allocate the user terminals to the various APs is the key to achieving this goal. The approach has been formulated as an integer programming problem with nonlinear constraints, which comes from a general but accurate characterisation of the WLAN. This general problem formulation has two implications: the formulation is widely applicable, but the nonlinearity makes it NP-hard. To solve this problem to optimality, we devised an exact algorithm based on a customised version of Benders' decomposition method. The computational results proved the ability to obtain remarkable power savings. In addition, the good performance of our algorithm in terms of solving times paves the way for its future deployment in real WLANs.

关键词： wireless LAN energy efficiency resource allocation optimisation mixed integer non-linear programming green networking network management

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A swarm intelligence graph-based pathfinding algorithm (SIGPA) for multi-objective route planning

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COMPUTERS & OPERATIONS RESEARCH 2021年 133卷 105358-105358页

作者： Ntakolia, Charis Iakovidis, Dimitris K. Univ Thessaly Sch Sci Dept Comp Sci & Biomed Informat Volos Greece

Personalized tourist route planning (TRP) and navigation are online or real-time applications whose mathematical modeling leads to complex optimization problems. These problems are usually formulated with mathematical programming and can be described as NP hard problems. Moreover, the state-of-the-art (SOA) path search algorithms do not perform efficiently in solving multi-objective optimization (MO) problems making them inappropriate for real-time processing. To address the above limitations and the need for online processing, a swarm intelligence graph-based pathfinding algorithm (SIGPA) for MO route planning was developed. SIGPA generates a population whose individuals move in a greedy approach based on A* algorithm to search the solution space from different directions. It can be used to find an optimal path for every graph-based problem under various objectives. To test SIGPA, a generic MOTRP formulation is proposed. A generic TRP formulation remains a challenge since it has not been studied thoroughly in the literature. To this end, a novel mixed binary quadratic programming model is proposed for generating personalized TRP based on multi-objective criteria and user preferences, supporting, also, electric vehicles or sensitive social groups in outdoor cultural environments. The model targets to optimize the route under various factors that the user can choose, such as travelled distance, smoothness of route without multiple deviations, safety and cultural interest. The proposed model was compared to five SOA models for addressing TRP problems in 120 various scenarios solved with CPLEX solver and SIGPA. SIGPA was also tested in real scenarios with A* algorithm. The results proved the effectiveness of our model in terms of optimality but also the efficiency of SIGPA in terms of computing time. The convergence and the fitness landscape analysis showed that SIGPA achieved quality solutions with stable convergence.

关键词： mixed integer non-linear programming Swarm intelligence algorithm Path search algorithm Convergence analysis Tourist route planning

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A two-stage Genetic Algorithm for joint coordination of spare parts inventory and planned maintenance under uncertain failures

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APPLIED SOFT COMPUTING 2022年 130卷

作者： Yu, Vincent F. Salsabila, Nabila Yuraisyah Siswanto, Nurhadi Kuo, Po-Hsun Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei 106 Taiwan Natl Taiwan Univ Sci & Technol Ctr Cyber Phys Syst Innovat Taipei 106 Taiwan Inst Teknol Sepuluh Nopember Dept Ind & Syst Engn Surabaya 60111 Indonesia

The main problem of spare parts management is to maintain the minimal requirement of stock keeping units kept. This research proposes a joint optimization model of multi-item multi-period spare parts inventory management and planned maintenance under uncertain failures in order to balance inventory cost and spare parts availability. This paper presents a mixed integer non-linear programming formulation of the inventory optimization model under a minimum and maximum inventory policy with stock review intervals. Some studies in the literature have considered aggregating spare parts inventory management as they assume that it will reduce the ordering cost. We consider both independent and aggregate spare parts inventory policies and then combine the formulation with the predictive maintenance interval, which is a replacement action due to uncertain failures under predefined distribution. Furthermore, a novel two-stage Genetic Algorithm is proposed as a sim-heuristic approach to deal with the non-linearity, combinations, and stochasticity of the problem and solve large-scale instances. In the end, we perform a computational study on some instances and a real-world case study to demonstrate the proposed approach's effectiveness and efficiency. The computational study shows that the independent policy results in lower cost than the aggregate policy, and the proposed Genetic Algorithm performs efficiently for large-scale problems.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Inventory management Planned maintenance Stochastic programming mixed integer non-linear programming Genetic algorithm Sim-heuristics

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Layout Optimization for Photovoltaic Panels in Solar Power Plants via a MINLP Approach

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2023年 1-14页

作者： Mignoni, Nicola Carli, Raffaele Dotoli, Mariagrazia Polytech Bari Dept Elect & Informat Engn I-70125 Bari Italy

Photovoltaic (PV) technology is one of the most popular means of renewable generation, whose applications range from commercial and residential buildings to industrial facilities and grid infrastructures. The problem of determining a suitable layout for the PV arrays, on a given deployment region, is generally non-trivial and has a crucial importance in the planning phase of solar plants design and development. In this paper, we provide a mixed integer non-linear programming formulation of the PV arrays' layout problem. First, we define the astronomical and geometrical models, considering crucial factors such as self-shadowing and irradiance variability, depending on the geographical position of the solar plant and yearly time window. Subsequently, we formalize the mathematical optimization problem, whose constraints' set is characterized by non-convexities. In order to propose a computationally tractable approach, we provide a tight parametrized convex relaxation. The resulting optimization resolution procedure is tested numerically, using realistic data, and benchmarked against the traditional global resolution approach, showing that the proposed methodology yields near-optimal solutions in lower computational time. Note to Practitioners-The paper is motivated by the need for efficient algorithmic procedures which can yield near-optimal solutions to the PV arrays layout problem. Due to the strong non-convexity of even simple instances, the existing methods heavily rely on global or stochastic solvers, which are computationally demanding, both in terms of resources and run-time. Our approach acts as a baseline, from which practitioners can derive more elaborate instances, by suitably modifying both the objective function and/or the constraints. In fact, we focus on the minimum set of necessary geometrical (e.g., arrays position model), astronomical (e.g., irradiance variation), and operational (e.g., power requirements) constraints which make the overall problem ha

关键词： Optimization Layout Sun Observers Mathematical models Azimuth Photovoltaic systems Photovoltaic solar power plants solar array layout non-convex optimization convexification parametrization mixed integer non-linear programming

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Capacitated facility location-allocation problem for wastewater treatment in an industrial cluster

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COMPUTERS & OPERATIONS RESEARCH 2021年 132卷 105338-105338页

作者： Chandra, Saurabh Sarkhel, Manish Vatsa, Amit Kumar Indian Inst Management Operat Management & Quantitat Tech Indore 453556 Madhya Pradesh India TA Pai Management Inst Operat & Decis Sci Manipal 576104 Karnataka India

We present a location-allocation problem for wastewater treatment in a cluster of processing units. The problem involves installing wastewater treatment plants of appropriate capacities at suitable locations and allocating processing units to these plants. The operational cost of treatment plants is a nonconvex function of wastewater volume and pollutant concentration. This problem is formulated as a non-convex mixed integer nonlinear programming (MINLP) problem. For the general class of this problem, solution strategies based on adapted McCormick envelopes and also piece-wise linear approximation are presented. For a special case of this problem, an exact convexification strategy is proposed and an outer approximation based branch-and-cut approach is presented as an exact solution method. For solving larger instances, we present a matheuristic solution method based on multi-start neighborhood search incorporated into a MINLP solution approach. A real-world case study is presented to illustrate the results of the model along with a multi-objective analysis.

关键词： Shared wastewater management Facility location mixed integer non-linear programming Outer approximation Multi-start neighborhood search McCormick envelopes

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Economic optimization of a combined heat and power plant: heat vs electricity

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Energy Procedia 2017年 116卷 138-151页

作者： Fabien Marty Sylvain Serra Sabine Sochard Jean-Michel Reneaume UNIV PAU & PAYS ADOUR LABORATOIRE DE THERMIQUE ENERGETIQUE ET PROCEDES-IPRA EA1932 64000 PAU FRANCE

This contribution presents the economical optimization of the parallel repartition between electric and heat production for geothermal application. The 350 m 3 /h flow of geothermal fluid, assimilated to liquid water at 185 °C , is then separated in two streams. Its reinjection temperature is fixed at 70 °C . An Organic Rankine Cycle (ORC) system is used to convert a part of geothermal energy into electricity. The refrigerant chosen is the R245fa. The different components of the ORC are sized in order to calculate the installation cost that depends on one characteristic dimension of each item (exchange surface for heat exchangers and power for the turbine and pumps). The operating cost is proportional to the installation cost. In this contribution, since we do not consider the detailed structural optimization of the District Heating Network (DHN), its investment cost is proportional to the supplied heat. The selling price of the electrical net power is a function of the recovered heat by the network. A mixed integer non-linear programming (MINLP) optimization is performed using the GAMS ® software. The problem is solved in order to determine the maximal profit of the global system. Results show that it is preferable to produce electricity alone but this is dependent on the choice of the price of sale of heat by the owner. The sell price from which it is more profitable to produce and to sell the heat is determined for each case. The optimization for each case shows that it is not easy to predict the final results and it justifies the use of optimization.

关键词： Combined heat power District heating network mixed integer non-linear programming Optimization Organic rankine cycle

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