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A mixed-integer linear programming model and a metaheuristic approach for the selection and allocation of land parcels problem

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2023年第4期30卷 1730-1754页

作者： Fernandez Gil, Alejandro Gomez Sanchez, Mariam Castro, Carlos Perez-Alonso, Alain Univ Tecn Federico Santa Maria Dept Informat Valparaiso Chile Univ Tecn Federico Santa Maria Dept Elect & Informat Concepcion Chile

This article is about the current agricultural scenario, where large-scale production causes large amounts of food to be transported to various points of consumption, causing substantial emissions of so-called greenhouse gases and increasing the carbon footprint. Land use optimization and land parcel allocation are essential areas of agriculture research that currently represent relevant challenges and are classified as combinatorial optimization problems. In this context, the Selection and Allocation of Land Parcels Problem (SA-LPP) is proposed;its goal is to optimize the selection and allocation of land parcels with rectangular shapes in small areas available for food production. We propose a reformulation of the SA-LPP as a variant of the two-dimensional orthogonal packing problem (2OPP), called Group-2OPP. This problem was solved through a mixed-integer linear programming (MILP) model, but due to the model complexity, we also propose a Greedy Randomized Adaptive Search Procedure metaheuristic approach. Some sensitivity analyses were performed as well to evaluate the impact of parameters on the solutions. Computational results show that the proposed metaheuristic outperforms the MILP model in terms of solution quality and computational times.

关键词： selection and allocation of land parcels problem agriculture combinatorial optimization mixed integer linear programming metaheuristic GRASP packing problem

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Design of efficient FIR filters with cyclotomic polynomial prefilters using mixed integer linear programming

Design of efficient FIR filters with cyclotomic polynomial p...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Woo Jin Oh Yong Hoon Lee Department of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon South Korea

ISBN: (纸本)0780331923

The cyclotomic polynomial (CP) prefilter design problem is formulated as an optimization problem with linear objective functions by applying the logarithm to the transfer function of the CP prefilter. Then this problem is solved by mixed integer linear programming (MILP). Design examples demonstrate that this method leads to more efficient cascaded FIR prefilter-equalizers than existing methods.

关键词： Finite impulse response filter Nonlinear filters Polynomials Equalizers Design methodology mixed integer linear programming Band pass filters Passband Design optimization Transfer functions

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Scheduling of discrete event systems using mixed integer linear programming

Scheduling of discrete event systems using mixed integer lin...

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International Workshop on Discrete Event Systems, WODES

作者： A. Kobetski M. Fabian Chalmers Automation Department of Signals and Systems Chalmers University of Technology Goteborg Sweden

To remain competitive, the modern industry strive for flexibility. Recently, a method for automatic generation of control code from a 3D simulation model of a flexible manufacturing system was developed. Finite automata and supervisory control theory (SCT) were used to guarantee the required behaviour of the system. This paper moves one step further. A method for automatic conversion between deterministic finite automata and mixed integer linear programming (MILP) formulation is presented. This allows to efficiently combine SCT and MILP to automatically generate time-optimal, collision-free and non-blocking working schedules

关键词： Discrete event systems mixed integer linear programming Automata Robot kinematics Robotics and automation Job shop scheduling Doped fiber amplifiers Optimal scheduling Manufacturing automation Flexible manufacturing systems

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A mixed-integer linear programming model for bulk grain blending and shipping

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2007年第2期107卷 555-571页

作者： Bilgen, Bilge Ozkarahan, Irem Dokuz Eylul Univ Dept Ind Engn TR-35100 Izmir Turkey

This paper addresses a blending and shipping problem faced by a company that manages a wheat supply chain. The problem involves the delivery of bulk products from loading ports to destination ports, which may be served by different vessel types. Since the products demanded by customers are mainly exported in bulk to overseas customers, the shipment planning is of great economic importance. The problem is formulated as a mixed-integer linear programming model. The objective function seeks to minimize the total cost including the blending, loading, transportation and inventory costs. Constraints on the system include blending and demand requirements, availability of original and blended products;as well as blending, loading, draft and vessel capacity restrictions. When solved, the model produces: (1) the quantity of each original product to be used to make blended products, (2) the quantity of each product to be loaded at each port and to be transported from each port to each customer, and (3) the number of vessels of each type to be hired in each time period. Numerical results are presented to demonstrate the feasibility of the real world bulk grain blending and shipping model. (C) 2006 Elsevier B.V. All rights reserved.

关键词： distribution planning blending maritime transportation supply chain management mixed integer linear programming

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A Novel Framework Based on mixed-integer linear programming to Restore a Disintegrated Power Grid after Cascading Failures

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IEEE LATIN AMERICA TRANSACTIONS 2021年第4期19卷 669-678页

作者： Beyza, Jesus Yusta, Jose M. Ruiz-Paredes, Hector F. Garcia-Paricio, Eduardo Inst Tecnol Morelia Programa Grad & Invest Ingn Elect Morelia 58120 Michoacan Mexico Univ Zaragoza Dept Ingn Elect Zaragoza 50009 Aragon Spain

Electric power systems are prone to disturbances and contingencies, which can trigger cascading failures with severe consequences for society. These undesirable events could disintegrate the electrical infrastructure in areas with disconnected elements. In this article, we propose a novel procedure to restore a collapsed power grid composed of multiple islands and isolated assets. The framework developed identifies the power lines to be closed during the electrical network recovery stages. In the latter, link overload limits and generation thresholds are taken into account. Two disintegrated networks based on the well-known IEEE 57-bus test system are built to demonstrate the performance of our proposal. In summary, this methodology provides a solution to recover the power system optimally and reliably.

关键词： Power system protection Power system faults Power grids mixed integer linear programming IEEE transactions Art Silicon compounds cascading failures power system security Resilience vulnerability

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Model Predictive Control of Central Chiller Plant With Thermal Energy Storage Via Dynamic programming and mixed-integer linear programming

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2015年第2期12卷 565-579页

作者： Deng, Kun Sun, Yu Li, Sisi Lu, Yan Brouwer, Jack Mehta, Prashant G. Zhou, MengChu Chakraborty, Amit Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Siemens Corp Corp Technol Princeton NJ 08540 USA New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA King Abdulaziz Univ Dept Elect & Comp Engn Jeddah 21413 Saudi Arabia NIST Gaithersburg MD 20899 USA Univ Calif Irvine Dept Mech & Aerosp Engn Irvine CA 92697 USA

This work considers the optimal scheduling problem for a campus central plant equipped with a bank of multiple electrical chillers and a thermal energy storage (TES). Typically, the chillers are operated in ON/OFF modes to charge TES and supply chilled water to satisfy the campus cooling demands. A bilinear model is established to describe the system dynamics of the central plant. A model predictive control (MPC) problem is formulated to obtain optimal set-points to satisfy the campus cooling demands and minimize daily electricity cost. At each time step, the MPC problem is represented as a large-scale mixed-integer nonlinear programming problem. We propose a heuristic algorithm to obtain suboptimal solutions for it via dynamic programming (DP) and mixed integer linear programming (MILP). The system dynamics is linearized along the simulated trajectories of the system. The optimal TES operation profile is obtained by solving a DP problem at every horizon, and the optimal chiller operations are obtained by solving an MILP problem at every time step with a fixed TES operation profile. Simulation results show desired performance and computational tractability of the proposed algorithm. Note to Practitioners-This work was motivated by the supervisory control need for a campus central plant. Plant operators have to decide a scheduling strategy to mix and match various chillers with a thermal energy storage to satisfy the campus cooling demands, while minimizing the operation cost. This work mathematically characterizes the system dynamics of a campus central plant and establishes a linear model to predict campus cooling load. It proposes a model predictive control (MPC) strategy to optimally schedule the campus central plant based on plant system dynamics and predicted campus cooling load. A heuristic algorithm is proposed to obtain suboptimal solutions for the MPC problem. The effectiveness and efficiency of the proposed approach are well demonstrated for the central pl

关键词： Central chiller plant dynamic programming heuristic algorithm mixed integer linear programming model predictive control supervisory control thermal energy storage

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mixed-integer linear programming and constraint programming formulations for solving distributed flexible job shop scheduling problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 142卷 106347-106347页

作者： Meng, Leilei Zhang, Chaoyong Ren, Yaping Zhang, Biao Lv, Chang Liaocheng Univ Sch Comp Sci Liaocheng 252059 Shandong Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Jinan Univ Sch Intelligent Syst Sci & Engn Zhuhai Campus Zhuhai 519070 Peoples R China

This paper intends to address the distributed flexible job shop scheduling problem (DFJSP) with minimizing maximum completion time (makespan). In order to solve this problem, we propose four mixed integer linear programming (MILP) models as well as a constraint programming (CP) model, among which four MILP models are formulated based on four different modeling ideas. MILP models are effective in solving small-scaled problems to optimality. DFJSP is NP-hard, therefore, we propose an efficient constraint programming (CP) model based on interval decision variables and domain filtering algorithms. Numerical experiments are conducted to evaluate the performance of the proposed MILP models and CP model. The results show that the sequence-based MILP model is the most efficient one, and the proposed CP model is effective in finding good quality solutions for the both the small-sized and large-sized instances. The CP model incomparably outperforms the state-of-the-art algorithms and obtains new best solutions for 11 benchmark problems. Moreover, the best MILP model and CP model have proved the optimality of 62 best-known solutions.

关键词： Distributed flexible job shop scheduling problem mixed integer linear programming Constraint programming Makespan

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A practical mixed integer linear programming based approach for unit commitment

A practical mixed integer linear programming based approach ...

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IEEE General Meeting Power& Energy Society

作者： G.W. Chang Y.D. Tsai C.Y. Lai J.S. Chung Department of Electrical Engineering National Chung Cheng University Chiayi Taiwan

This paper presents a practical mixed integer linear programming (MILP) based approach for unit commitment (UC), which is suitable for both traditional and deregulated environments. In general, the UC problem is complicated large-scale, combinatorial, and non-convex in nature, it is very difficult to solve by conventional approaches to achieve both solution accuracy and efficiency. With the recent development of solution techniques, there is a trend to tackle the UC problem by using MILP approaches. In this paper the authors propose a detailed procedure to formulate the UC problem in MILP manners. The problems are then solved via a state-of-the-art optimization package. The usefulness of the proposed solution technique is illustrated by testing the problem with actual system data. The solution obtained not only gives the unit on/off states and MW schedules, but also provides marginal price information associated with system constraints such as load demand requirement to assist strategic bidding in the power market.

关键词： mixed integer linear programming Power markets Cost function Fuels Packaging integer linear programming Large-scale systems System testing Helium Power generation economics

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A mixed integer linear programming Model of a Steelmaking and Casting Plant

A Mixed Integer Linear Programming Model of a Steelmaking an...

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IEEE Annual Conference on Decision and Control

作者： Maria Pia Fanti Gabriella Stecco Walter Ukovich Department of Electrical and Electronic Engineering Polytechnic of Bari Bari Italy Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (纸本)9781467357159

This paper deals with the Steelmaking and Casting phases of a real integrated plant. We focus on the scheduling of the casts on the machines of the process and on the cranes that perform the internal transport. The casting phase is made by Continuous Casting and Ingot Casting machines. A mixed integer linear programming model is presented for the schedule of operations, with the objective of minimizing the makespan. The model is divided into four sub-models: the steelmaking and casting processes, the cranes, the continuous casting machines and the ingot casting machines. An example is presented to show the application of the proposed model.

关键词： Steelmaking ingots mixed integer linear programming casting plant machine Continuous casting machinery scheduling operation

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Fast Topology Identification of AC / DC Hybrid Distribution Network Based on mixed integer linear programming

Fast Topology Identification of AC / DC Hybrid Distribution ...

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Cyber-Energy Systems and Intelligent Energy (ICCSIE), International Conference on

作者： Shiyao Hu Xichun Feng Xiaofan Kang Yuntao Ju Jing Jiang Economic and Technical Research Institute State Grid Hebei Electric Power Co. Ltd Shijiazhuang China School of Electrical and Control Engineering North China University of Technology Beijing China State Grid Economic and Technological Research Institute Co. Ltd Beijing China

ISBN: (数字)9798350373318

ISBN: (纸本)9798350373325

Topology identification is crucial for advanced analysis such as state estimation in hybrid AC/DC distribution networks. Traditional topology identification methods based on data statistics lack accuracy, and optimization-based methods exhibit low efficiency. To address these issues, a topology identification method based on mixed-integer linear programming is proposed. Initially, the normalized Lagrange multiplier is utilized to identify suspicious measurements, forming a set of suspicious measurements to reduce the number of integer variables to be determined. Subsequently, a linearization method for network constraints in hybrid AC/DC distribution networks is introduced to transform the topology identification problem into a mixed-integer linear programming model. The simulation results demonstrate that by constructing a set of suspicious measurements and linearizing network constraints, the efficiency of solving the problem is significantly improved while ensuring the accuracy of identification.

关键词： Accuracy Network topology Simulation Measurement uncertainty Distribution networks Transforms Time measurement Topology mixed integer linear programming State estimation

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