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第33届中国控制与决策会议

作者： Junling Cai Ning Zhang Yingli Wang Academy of Military Science Center of Assessment and Demonstration Research School of Economics and Management Beihang University

In this paper,the problem of aircraft conflict avoidance is studied arising in Air Traffic Management *** initial configuration of all aircraft including position,velocities,heading angles,altitude and flight trajectories are known,and they are assumed to fly within a shared three-dimensional *** aim of the problem is to find an optimal conflict avoidance strategy for the aircraft so that various conflicts situations can be avoided.A conflict occurs when the relative distance between any pairs of aircraft is less than the minimal safe separation during their *** order to ensure the safety of aircraft flight,a mixed integer nonlinear programming model(MINLP) for solving the three-dimensional conflict avoidance problem involving multiple aircrafts is proposed in this paper,where the aircraft are allowed to change simultaneously heading angle and velocity to achieve the *** illustration verifies the effectiveness of the *** optimal solution of the problem can be obtained easily in a small computational time by using a standard global optimization solver to solve the proposed MINLP model.

关键词： Air Traffic Management mixed integer nonlinear programming optimal conflict avoidance strategy global optimization

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3D Loading Problem Formulation Using mixed integer nonlinear programming

<i>3D</i> Loading Problem Formulation Using Mixed Integer No...

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： Osman, Mojahid Saeed Ram, Bala King Fand Univ Petr & Minerals Dept Syst Engn Dhahran Saudi Arabia Nort Carolina A&T State Univ Dept Ind & Syst Engn Greensboro NC USA

ISBN: (纸本)9781479964109

The manufacturing of different types of cylindrical parts requires loading of parts into baskets for heat treatment operation. This loading process is complex and involves issues relating to geometry, and heterogeneity in the parts and in their processing requirements. The parts loaded for heat treatment often do not utilize the available capacity adequately because layer-loading is accomplished by operator ingenuity. Productivity in heat treatment operation can be increased by improving utilization, which is determined by the loading process. This paper describes the development mathematical model using mixed integer nonlinear formulation for loading of cylindrical parts into baskets. The mathematical modeling considers the exact location of parts to be loaded on the layers with the primary objective of minimizing unutilized volume of the baskets.

关键词： Packing problem mixed integer nonlinear programming

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Optimal Placement of SVC Based on Line Flow Base Equation Using mixed integer nonlinear programming

Optimal Placement of SVC Based on Line Flow Base Equation Us...

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Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Etemad, Reza Navabi, Reza Shayanfar, Heidar Ali Iran Univ Sci & Technol Dept Elect Engn Tehran Iran Iran Univ Sci & Technol Ctr Excellence Power Syst Automat & Operat Dept Elect Engn Tehran Iran

ISBN: (纸本)9781424448135

In this paper a novel approach to determine optimal location, number and initial compensation level of the SVC in a power system is presented. mixed integer nonlinear programming (MINLP) is used for this purpose as a useful technique for combinatorial optimization over integers and variables. This technique can provide a fast approach as well as high computational efficiency even in solving complex optimization problems. Previous works used DC power flow that has well known limitations such as reactive power balance and reactive power loss ignorance. This paper uses novel Line Flow Based (LFB) equation that employs line power flow (instead of line current) and square of the bus voltages as variables. Since control variables such as line active and reactive power flow figure directly in formulation, handling the control action of the Flexible Alternating Current Transmission Systems (FACTS) devices is directly and easily implemented. The objectives of this paper are increasing system loadability and decreasing power losses and VAr generation cost by finding the optimal location, number and initial setting of the SVCs.

关键词： FACTS allocation SVC mixed integer nonlinear programming Line Flow Based Equations

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The Multiplicative Weights Update Algorithm for mixed integer nonlinear programming: Theory, Applications, and Limitations

The Multiplicative Weights Update Algorithm for Mixed Intege...

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作者： Luca Mencarelli Ecole Polytechnique

学位级别：博士

This thesis presents a new algorithm for mixed integer nonlinear programming, inspi- red by the Multiplicative Weights Update frame- work and relying on a new class of reformulations, called the pointwise reformulations. mixed integer nonlinear programming is a hard and fascinating topic in Mathematical Optimiza- tion both from a theoretical and a computational viewpoint. Many real-world problems can be cast this general scheme and, usually, are quite challen- ging in terms of efficiency and solution accuracy with respect to the solving procedures. The thesis is divided in three main parts: a fore- word consisting in Chapter 1, a theoretical founda- tion of the new algorithm in Chapter 2, and the ap- plication of this new methodology to two real-world optimization problems, namely the Mean-Variance Portfolio Selection in Chapter 3, and the Multiple nonlinear Separable Knapsack Problem in Chap- ter 4. Conclusions and open questions are drawn in Chapter 5.

关键词： mixed integer nonlinear programming Multiplicative Weights Update Algorithm Mean-Variance Portfolio Multiple nonlinear Knapsack Problem

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Optimal Configuration of Gas Solid Separation Equipment Using mixed integer nonlinear programming

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ATMOSPHERE 2022年第11期13卷 1831-1831页

作者： Failaka, Muhamad Fariz Madhuranthakam, Chandra Mouli R. Yetilmezsoy, Kaan Almansoori, Ali Elkamel, Ali Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada Abu Dhabi Univ Dept Chem Engn POB 59911 Abu Dhabi U Arab Emirates Yildiz Tech Univ Fac Civil Engn Dept Environm Engn TR-34220 Istanbul Turkey Khalifa Univ Dept Chem Engn POB 59911 Abu Dhabi U Arab Emirates

The separation of solid particles from gas-solid process streams is an important unit operation in many chemical processes. Out of the many different types of separation equipment that are used for gas-solid separation, cyclone separators are widely used for their operational flexibility, efficiency and capital cost. This study focused on the design of an optimal configuration for several cyclones used in a fertilizer plant. The granulation step in the fertilizer plant leads to using different size cyclones and a different number of cyclones in series or parallel or a mix of both arrangements. A mixed integer nonlinear programming (MINLP) model is formulated to find the best cyclone arrangement with the optimal number of cyclones and dimensions from several combinations of 1D3D and 2D2D cyclones arranged in parallel-series for a high volume and heavy loading of solid particles. The objective function was to minimize the total cost, including the operating cost and the capital cost. The results indicated that a maximum of 90% efficiency is achieved with a parallel-series arrangement of 1D3D and 2D2D cyclones to be an optimal configuration for the maximum reduction in pollution level.

关键词： cyclone separators general algebraic modeling system mixed integer nonlinear programming modeling optimization

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Bilevel mixed-integer nonlinear programming for integrated scheduling in a supply chain network

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6-Sup期22卷 15517-15532页

作者： Yang, Jianchao Guo, Feng Luo, Li Ye, Xiaoming Sichuan Univ Business Sch Chengdu Sichuan Peoples R China Sichuan Univ Coll Comp Sci Chengdu Sichuan Peoples R China Chengdu Univ Informat Technol Sch Cybersecur Chengdu Sichuan Peoples R China

An integrated scheduling problem under a make-to-order supply chain network is addressed. This problem considers integrated production and transportation scheduling with realistic supply chain features such as unrelated parallel shop and product batch-based transportation. The mathematical model for this problem is presented, which is formulated as a bilevel mixed-integer nonlinear program. A novel bilevel evolutionary optimization model based on memetic algorithm is proposed to resolve this problem because the problem is hard-to-tackle for mathematical programming techniques and traditional intelligent techniques. The effectiveness of the proposed optimization model is validated through a series of numerical experiments. The experimental results also confirmed that the proposed optimization model is superior to other three intelligent optimization models.

关键词： Make-to-order supply chain scheduling mixed integer nonlinear programming Bilevel programming Memetic algorithm Bilevel evolutionary algorithms

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Solving mixed-integer nonlinear programming problems using improved genetic algorithms

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KOREAN JOURNAL OF CHEMICAL ENGINEERING 2011年第1期28卷 32-40页

作者： Wasanapradit, Tawan Mukdasanit, Nalinee Chaiyaratana, Nachol Srinophakun, Thongchai Kasetsart Univ Dept Chem Engn Fac Engn Bangkok 10900 Thailand King Mongkuts Univ Technol Fac Engn Dept Chem Engn Bangkok 10140 Thailand King Mongkuts Univ Technol Fac Engn Dept Chem Engn Bangkok 10800 Thailand Natl Ctr Excellence Petr Petrochem & Adv Mat Bangkok 10330 Thailand

This paper proposes a method for solving mixed-integer nonlinear programming problems to achieve or approach the optimal solution by using modified genetic algorithms. The representation scheme covers both integer and real variables for solving mixed-integer nonlinear programming, nonlinear programming, and nonlinear integer programming. The repairing strategy, a secant method incorporated with a bisection method, plays an important role in converting infeasible chromosomes to feasible chromosomes at the constraint boundary. To prevent premature convergence, the appropriate diversity of the structures in the population must be controlled. A cross-generational probabilistic survival selection method (CPSS) is modified for real number representation corresponding to the representation scheme. The efficiency of the proposed method was validated with several numerical test problems and showed good agreement.

关键词： Genetic Algorithms mixed integer nonlinear programming Repairing Strategy CPSS Modified Genetic Algorithms

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An improved Estimation of Distribution Algorithm for Solving Constrained mixed-integer nonlinear programming Problems

An improved Estimation of Distribution Algorithm for Solving...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Molina Perez, Daniel Alfredo Portilla-Flores, Edgar Mezura-Montes, Efren Vega-Alvarado, Eduardo Inst Politecn Nacl CIDETEC Ciudad De Mexico Mexico Inst Politecn Nacl UPIIT Tlaxcala Mexico Univ Veracruz Artificial Intelligence Res Ctr Veracruz Veracruz Mexico

ISBN: (数字)9781665467087

ISBN: (纸本)9781665467087

In a mixed-integer nonlinear programming problem, integer restrictions divide the feasible region into discontinuous feasible parts with different sizes. Evolutionary Algorithms (EAs) are usually vulnerable to being trapped in larger discontinuous feasible parts. In this work, an improved version of an Estimation of Distribution Algorithm (EDA) is developed, where two new operations are proposed. The first one establishes a link between the learning-based histogram model and the s-constrained method. Here, the constraint violation level of the s-constrained method is used to explore the smaller discontinuous parts and form a better statistical model. The second operation is the hybridization of the EDA with a mutation operator to generate offspring from both the global distribution information and the parent information. A benchmark is used to test the performance of the improved proposal. The results indicated that the proposed approach shows a better performance against other tested EAs. This new proposal solves to a great extent the influence of the larger discontinuous feasible parts, and improve the local refinement of the real variables.

关键词： estimation of distribution algorithm evolutionary algorithms integer restriction handling mixed integer nonlinear programming

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A hybrid algorithm framework for heat exchanger networks synthesis considering the optimal locations of multiple utilities

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CHEMICAL ENGINEERING SCIENCE 2025年 301卷

作者： Yang, Lu Yang, Zekun Akram, Naeem Chang, Chenglin Mo, Wenlong Shen, Weifeng Zhang, Nan Smith, Robin Chongqing Univ Sch Chem & Chem Engn Chongqing 400044 Peoples R China Univ Manchester Ctr Proc Integrat Dept Chem Engn Manchester England Minhaj Univ Lahore Sch Chem Engn Lahore 54000 Punjab Pakistan Xinjiang Univ Coll Chem Engn Key Lab Oil & Gas Fine Chem Minist Educ & Xinjiang Uygur Autonomous Reg Urumqi 830046 Peoples R China Xinjiang Yihua Chem Co Ltd Changji 831100 Peoples R China

This work focuses on heat exchanger networks (HENs) synthesis (HENS) considering the optimal locations of multiple utilities. Based on an extended stage-wise superstructure where available heaters and coolers are placed at all stages, HENS is modeled as a computationally-hard mixed integer nonlinear programming (MINLP) problem. To obtain high-quality solutions, we propose a new hybrid algorithm framework that combines deterministic algorithm (commercial solver) and genetic algorithm (GA) without the use of penalty functions. In the outer level of the framework, GA is employed to optimize the integer variables which represent the existences of matches between process streams as well as the available heaters and coolers at intermediate stages. In the inner level, a reduced-size MINLP model is built to minimize the total annualized costs (TACs) of HENs generated in the outer level. We also propose three new sets to exclude infeasible stream matches, thereby the HENs generated in the outer level are all feasible and our GA does not need any penalty terms. Four literature examples are tested and optimal solutions with lower TACs are obtained within acceptable computing time compared to solutions reported in literature.

关键词： Heat exchanger networks Hybrid algorithm framework Locations of utilities Superstructure mixed integer nonlinear programming

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Dependency-aware task collaborative offloading and resource allocation in UAV enabled edge computing

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2025年第3期18卷 1-19页

作者： Huang, Zhenqi Kuang, Zhufang Xu, Bin Bi, Yuanguo Liu, Anfeng Cent South Univ Coll Comp & Math Shaoshan South Rd Changsha 410004 Hunan Peoples R China Northeastern Univ Sch Comp Sci & Engn Wenhua Rd Shenyang 110819 Peoples R China Cent South Univ Sch Elect Informat Lushan South Rd Changsha 410010 Hunan Peoples R China

Edge computing, a new wireless communications technology, can provide abundant resources for computing and storage. Recently, it is a challenging problem to jointly consider the offloading and resource allocation of generally dependent tasks in multi Unmanned Aerial Vehicles (UAVs) multi Terminal Devices (TDs) edge computing system. In this paper, the joint problem of offloading decisions, collaborative decisions and resource allocation of general dependent tasks is investigated, considering and highlighting the cooperation between TDs. The corresponding optimization problem, which is a mixed integer nonlinear programming problem, is formulated. To make this problem solved, an iterative method based on Deep Reinforcement Learning (DRL) and Convex optimization is proposed to decompose the original problem into two subproblems. Given the resource allocation scheme, the Deep Q network (DQN) algorithm is employed to solve the offloading and collaborative decisions of all tasks. Then, given the offloading decision and cooperation decision of all tasks, the convex optimization algorithm is used to solve the optimal resource allocation scheme in the UAV enabled edge computing system. Two subproblems iterative alternately. The simulation results demonstrated that our proposed method can significantly reduce the system energy consumption compared to other schemes.

关键词： Deep reinforcement learning mixed integer nonlinear programming UAV Task dependency Resource allocation

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