فهرست مقالات Discrete optimization

• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  1 - Sizing optimization of truss structures with discrete design variables using combined PSO algorithm with Special Particles Method
  Ali Gheibi Reza SojoudiZadeh Hadi Azizian Mahdi Gheibi
  10.22094/joie.2024.1973228.2014
  This paper proposes a modified particle swarm optimization (MPSO) algorithm for discrete sizing optimization of truss structures. The original particle swarm optimization (PSO) is a population-based metaheuristic that fluctuates the search agents about the best solution چکیده کامل

  This paper proposes a modified particle swarm optimization (MPSO) algorithm for discrete sizing optimization of truss structures. The original particle swarm optimization (PSO) is a population-based metaheuristic that fluctuates the search agents about the best solution based on Eberhart functions. The efficiency of the PSO in solving standard optimization problems of well-known problems of truss structures has been demonstrated in literature. However, its performance in tackling the discrete optimization problems of truss structures is not competitive compared with the recent existing metaheuristic algorithms. In the framework of the proposed MPSO a number of worst solutions of the current population is replaced by some variants of the global best solution found so far. Moreover, an efficient mutation operator is added to the algorithm that reduces the probability of getting stuck in local optima. The efficiency of the proposed MPSO is illustrated through two benchmark optimization problems of truss structures. پرونده مقاله
• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  2 - A new method for solving of the Graph Coloring Problem based on a fuzzy logic and whale optimization algorithm
  طاها مصطفایی فرزین مدرس خیابانی نیما جعفری نویمی پور بهروز دانشیان
  Abstract: In recent years, Graph Coloring Problem (GCP) is one of the main optimization problems from literature. Many real world problems interacting with changing environments can be modeled by dynamic graphs. Graph vertex coloring with a given number of colors is a w چکیده کامل

  Abstract: In recent years, Graph Coloring Problem (GCP) is one of the main optimization problems from literature. Many real world problems interacting with changing environments can be modeled by dynamic graphs. Graph vertex coloring with a given number of colors is a well-known and much-studied NP-hard problem. Meta-heuristic algorithms are a good choice to solve GCP because they are suitable for problems with NP-hard complexity. However, in many previously proposed algorithms, there are common problems such as runtime algorithm and low convergence of algorithm. Therefore, in this paper, we propose the Fuzzy Whale Optimization Algorithm (FWOA), a variety of basic Whale Optimization Algorithm (WOA), to improve runtime and convergence of algorithm in the GCP. Since WOA at first was introduced for solving continuous problem, we need a discrete WOA. Hence, to use FWOA to discrete search space, the standard arithmetic operators such as addition, subtraction and multiplication extant in FWOA encircling prey, exploitation phase and exploration phase operators based on distance’s theory needs to be redefined in the discrete space. Parameters p and r, are defined randomly in the WOA algorithm in FWOA algorithm defined as fuzzy and are selected in fuzzy tragedy. A set of graph coloring benchmark problems are solved and their performance are compared with some well-known heuristic search methods. Results illustrate that FWOA algorithm are the original focus of this work and in most cases success rate is nearly 100% and the runtime and convergence algorithm has been improved on some graphs. But as we have illustrated that comparison with other manners, we cannot deduce that our algorithm is the best in all instance of graphs. It can be said that a proposed algorithm is able to compete with other algorithms in this context. Obtained results approved the high performance of proposed method. پرونده مقاله
• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  3 - A dynamic programming approach for solving nonlinear knapsack problems
  E Jahangiri F Ghassemi-Tari
  Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these pr چکیده کامل

  Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these problems. Despite the power of this solu-tion approach, it computationally performs very slowly when the solution space of the problems grows rap-idly. In this paper the authors developed a procedure for improving the computational efficiency of the dy-namic programming for solving KNP. They incorporate three routines; the imbedded state, surrogate con-straints, and bounding scheme, in the dynamic programming solution approach and developed an algorithmic routine for solving the KNP. An experimental study for comparing the computational efficiency of the pro-posed approach with the general dynamic programming approach is also presented. پرونده مقاله
• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  4 - A ($2-\varepsilon$)-approximation ratio for vertex cover problem on special graphs
  N. Yekezare M. Zohrehbandian M. Maghasedi
  10.30495/jlta.2023.703516
  ‎The vertex cover problem is a famous combinatorial problem‎, ‎and its complexity has been heavily studied‎. ‎It is known that it is hard to approximate to within any constant factor better than $2$‎, ‎while a $2$-approximation for it can be چکیده کامل

  ‎The vertex cover problem is a famous combinatorial problem‎, ‎and its complexity has been heavily studied‎. ‎It is known that it is hard to approximate to within any constant factor better than $2$‎, ‎while a $2$-approximation for it can be trivially obtained‎. ‎In this paper‎, ‎new properties and new techniques are introduced which lead to approximation ratios smaller than $2$ on special graphs;‎ ‎e.g‎. ‎graphs for which their maximum cut values are less than $0.999|E|$‎. ‎In fact‎, ‎we produce a ($1.9997$)-approximation ratio on graph $G$‎, ‎where the ($0.878$)-approximation algorithm of the Goemans-Williamson for the maximum cut problem on $G$ produces a value smaller than $0.877122|E|$‎. پرونده مقاله