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A branch-and-bound algorithm for multi-dimensional quadratic 0-1 knapsack problems 被引量:2
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作者 孙娟 盛红波 孙小玲 《Journal of Shanghai University(English Edition)》 CAS 2007年第3期233-236,共4页
In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding ... In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding feasible solutions. The Lagrangian relaxations were solved with the maximum-flow algorithm and the Lagrangian bounds was determined with the outer approximation method. Computational results show the efficiency of the proposed method for multi-dimensional quadratic 0-1 knapsack problems. 展开更多
关键词 multi-dimensional quadratic 0-1 knapsack problem branch-and-bound method Lagrangian relaxation outer approximation surrogate constraint.
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Chaotic Neural Network Technique for "0-1" Programming Problems 被引量:1
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作者 王秀宏 乔清理 王正欧 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2003年第4期99-105,共7页
0-1 programming is a special case of the integer programming, which is commonly encountered in many optimization problems. Neural network and its general energy function are presented for 0-1 optimization problem. The... 0-1 programming is a special case of the integer programming, which is commonly encountered in many optimization problems. Neural network and its general energy function are presented for 0-1 optimization problem. Then, the 0-1 optimization problems are solved by a neural network model with transient chaotic dynamics (TCNN). Numerical simulations of two typical 0-1 optimization problems show that TCNN can overcome HNN's main drawbacks that it suffers from the local minimum and can search for the global optimal solutions in to solveing 0-1 optimization problems. 展开更多
关键词 neural network chaotic dynamics 0-1 optimization problem.
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An Improved Binary Wolf Pack Algorithm Based on Adaptive Step Length and Improved Update Strategy for 0-1 Knapsack Problems
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作者 Liting Guo Sanyang Liu 《国际计算机前沿大会会议论文集》 2017年第2期105-106,共2页
Binary wolf pack algorithm (BWPA) is a kind of intelligence algorithm which can solve combination optimization problems in discrete spaces.Based on BWPA, an improved binary wolf pack algorithm (AIBWPA) can be proposed... Binary wolf pack algorithm (BWPA) is a kind of intelligence algorithm which can solve combination optimization problems in discrete spaces.Based on BWPA, an improved binary wolf pack algorithm (AIBWPA) can be proposed by adopting adaptive step length and improved update strategy of wolf pack. AIBWPA is applied to 10 classic 0-1 knapsack problems and compared with BWPA, DPSO, which proves that AIBWPA has higher optimization accuracy and better computational robustness. AIBWPA makes the parameters simple, protects the population diversity and enhances the global convergence. 展开更多
关键词 BINARY WOLF PACK ALGORITHM 0-1 knapsack problem ADAPTIVE step length Update strategy
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Big Data Flow Adjustment Using Knapsack Problem
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作者 Eyman Yosef Ahmed Salama M. Elsayed Wahed 《Journal of Computer and Communications》 2018年第10期30-39,共10页
The advancements of mobile devices, public networks and the Internet of creature huge amounts of complex data, both construct & unstructured are being captured in trust to allow organizations to produce better bus... The advancements of mobile devices, public networks and the Internet of creature huge amounts of complex data, both construct & unstructured are being captured in trust to allow organizations to produce better business decisions as data is now pivotal for an organizations success. These enormous amounts of data are referred to as Big Data, which enables a competitive advantage over rivals when processed and analyzed appropriately. However Big Data Analytics has a few concerns including Management of Data, Privacy & Security, getting optimal path for transport data, and Data Representation. However, the structure of network does not completely match transportation demand, i.e., there still exist a few bottlenecks in the network. This paper presents a new approach to get the optimal path of valuable data movement through a given network based on the knapsack problem. This paper will give value for each piece of data, it depends on the importance of this data (each piece of data defined by two arguments size and value), and the approach tries to find the optimal path from source to destination, a mathematical models are developed to adjust data flows between their shortest paths based on the 0 - 1 knapsack problem. We also take out computational experience using the commercial software Gurobi and a greedy algorithm (GA), respectively. The outcome indicates that the suggest models are active and workable. This paper introduced two different algorithms to study the shortest path problems: the first algorithm studies the shortest path problems when stochastic activates and activities does not depend on weights. The second algorithm studies the shortest path problems depends on weights. 展开更多
关键词 0 - 1 KNAPSACK problem BIG DATA BIG DATA ANALYTICS BIG DAO TA Inconsistencies
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Nonconvex Quadratic Programming Method for k-Coloring Problem:Algorithm and Computation
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作者 Cao Jiaming(Department of Transportation Engineering) ,Southwest Jiaotong University,Chengdu 610031, China 《Journal of Modern Transportation》 1994年第2期138-145,共8页
In this paper, we consider the socalled k-coloring problem in general case.Firstly, a special quadratic 0-1 programming is constructed to formulate k-coloring problem. Secondly, by use of the equivalence between above... In this paper, we consider the socalled k-coloring problem in general case.Firstly, a special quadratic 0-1 programming is constructed to formulate k-coloring problem. Secondly, by use of the equivalence between above quadratic0-1 programming and its relaxed problem, k-coloring problem is converted intoa class of (continuous) nonconvex quadratic programs, and several theoreticresults are also introduced. Thirdly, linear programming approximate algorithmis quoted and verified for this class of nonconvex quadratic programs. Finally,examining problems which are used to test the algorithm are constructed andsufficient computation experiments are reported. 展开更多
关键词 k-coloring problem quadratic 0-1 programming relaxed equivalence nonconvex quadratic programming linear programming approximatealgorithm
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高维0-1瓶颈问题的动态规划算法
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作者 罗宗俊 《数值计算与计算机应用》 CSCD 2013年第1期38-46,共9页
在本文中,我们通过一个实际问题归纳出一个数学模型(正文中的模型Ⅰ),并通过新变量的引用,韩模型Ⅰ转化成一个高维0-1瓶颈规划(正文中的模型Ⅱ).对模型Ⅱ,我们建立了求模型Ⅱ最优解的动态规划算法(带有阀值Q).该算法与普通动态规划相比... 在本文中,我们通过一个实际问题归纳出一个数学模型(正文中的模型Ⅰ),并通过新变量的引用,韩模型Ⅰ转化成一个高维0-1瓶颈规划(正文中的模型Ⅱ).对模型Ⅱ,我们建立了求模型Ⅱ最优解的动态规划算法(带有阀值Q).该算法与普通动态规划相比大大节约了运算量.最后指出了该算法对0-1瓶颈问题的求解具有一定的普遍性. 展开更多
关键词 0-1瓶颈问题 动态规划 阀值
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Dynamic Weapon Target Assignment Based on Intuitionistic Fuzzy Entropy of Discrete Particle Swarm 被引量:17
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作者 Yi Wang Jin Li +1 位作者 Wenlong Huang Tong Wen 《China Communications》 SCIE CSCD 2017年第1期169-179,共11页
Aiming at the problems of convergence-slow and convergence-free of Discrete Particle Swarm Optimization Algorithm(DPSO) in solving large scale or complicated discrete problem, this article proposes Intuitionistic Fuzz... Aiming at the problems of convergence-slow and convergence-free of Discrete Particle Swarm Optimization Algorithm(DPSO) in solving large scale or complicated discrete problem, this article proposes Intuitionistic Fuzzy Entropy of Discrete Particle Swarm Optimization(IFDPSO) and makes it applied to Dynamic Weapon Target Assignment(WTA). First, the strategy of choosing intuitionistic fuzzy parameters of particle swarm is defined, making intuitionistic fuzzy entropy as a basic parameter for measure and velocity mutation. Second, through analyzing the defects of DPSO, an adjusting parameter for balancing two cognition, velocity mutation mechanism and position mutation strategy are designed, and then two sets of improved and derivative algorithms for IFDPSO are put forward, which ensures the IFDPSO possibly search as much as possible sub-optimal positions and its neighborhood and the algorithm ability of searching global optimal value in solving large scale 0-1 knapsack problem is intensified. Third, focusing on the problem of WTA, some parameters including dynamic parameter for shifting firepower and constraints are designed to solve the problems of weapon target assignment. In addition, WTA Optimization Model with time and resource constraints is finally set up, which also intensifies the algorithm ability of searching global and local best value in the solution of WTA problem. Finally, the superiority of IFDPSO is proved by several simulation experiments. Particularly, IFDPSO, IFDPSO1~IFDPSO3 are respectively effective in solving large scale, medium scale or strict constraint problems such as 0-1 knapsack problem and WTA problem. 展开更多
关键词 intuitionistic fuzzy entropy discrete particle swarm optimization algorithm 0-1 knapsack problem weapon target assignment
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Weekly Fleet Assignment Model and Algorithm 被引量:1
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作者 朱星辉 朱金福 巩在武 《Journal of Southwest Jiaotong University(English Edition)》 2007年第3期231-235,共5页
A 0-1 integer programming model for weekly fleet assignment was put forward based on linear network and weekly flight scheduling in China. In this model, the objective function is to maximize the total profit of fleet... A 0-1 integer programming model for weekly fleet assignment was put forward based on linear network and weekly flight scheduling in China. In this model, the objective function is to maximize the total profit of fleet assignment, subject to the constraints of coverage, aircraft flow balance, fleet size, aircraft availability, aircraft usage, flight restriction, aircraft seat capacity, and stopover. Then the branch-and-bound algorithm based on special ordered set was applied to solve the model. At last, a real- wofld case study on an airline with 5 fleets, 48 aircrafts and 1 786 flight legs indicated that the profit increase was ¥ 1 591276 one week and the running time was no more than 4 rain, which shows that the model and algorithm are fairly good for domestic airline. 展开更多
关键词 Flight scheduling Fleet assignment problem 0-1 Integer programming model Branch-and-bound algorithm
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A New Searching Strategy for the Lost Plane Based on RBF Neural Network Model and Global Optimization Model
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作者 Yiqing YU 《International Journal of Technology Management》 2015年第4期126-128,共3页
In this paper, we construct two models for the searching task for a lost plane. Model 1 determines the searching area. We predict the trajectory of floats generated after the disintegration of the plane by using RBF n... In this paper, we construct two models for the searching task for a lost plane. Model 1 determines the searching area. We predict the trajectory of floats generated after the disintegration of the plane by using RBF neural network model, and then determine the searching area according to the trajectory. With the pass of time, the searching area will also be constantly moving along the trajectory. Model 2 develops a maritime search plan to achieve the purpose of completing the search in the shortest time. We optimize the searching time and transform the problem into the 0-1 knapsack problem. Solving this problem by improved genetic algorithm, we can get the shortest searching time and the best choice for the search power. 展开更多
关键词 the trajectory of floats RBF neural network model Global optimization model 0-1 knapsack problem improved geneticalgorithm
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