In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition...

Stochastic optimization methods such as evolutionary algorithms and Markov Chain Monte Carlo methods usually involve a Markov search of the optimization domain. Evolutionary annealing is an evolutionary algorithm that leverages all the information gathered by previous queries to the cost function. Evolutionary annealing can be viewed either as simulated annealing with improved sampling or as a ...

The Robust Coloring Problem (RCP) is a generalization of the well-known Graph Coloring Problem where we seek for a solution that remains valid when extra edges are added. The RCP is used in scheduling of events with possible last-minute changes and study frequency assignments of the electromagnetic spectrum. This problem has been proved as NP-hard and in instances larger than 30 vertices, meta-...

Quantum annealing is a generic algorithm using quantum-mechanical fluctuations to search for the solution of an optimization problem. The present paper first reviews the fundamentals of quantum annealing and then reports on preliminary results for an alternative method. The review part includes the relationship of quantum annealing with classical simulated annealing. We next propose a novel qua...

This paper presents a parallel simulated annealing algorithm for solving the problem of mapping irregular parallel programs onto homogeneous processor arrays with regular topology. The algorithm constructs and uses joint transformations. These transformations guarantee a high degree of parallelism that is bounded below by d jNpj deg(Gp)+1 e, where jN p j is the number of task nodes in the mappe...

− In this paper, we propose a Simulated Annealing PolyClonal Selection Algorithm (SAPCSA) for Traveling Salesman Problems (TSP). By introducing a simulated annealing (SA) strategy to the PolyClonal Selection Algorithm (PCSA), the SAPCSA integrate the characteristics of both SA and PCSA. Numerous instances have been simulated to verify the proposed algorithm.

The first polynomial-time algorithm to approximate (with arbitrary precision) the permanent of a non-negative matrix was presented by Jerrum, Sinclair and Vigoda. They designed a simulated annealing algorithm with a running time of O∗(n26) for 0/1 matrices. Subsequently, they improved their analysis, resulting in a O∗(n10) time algorithm. We present a O∗(n7) time algorithm. Our improvement come...

introduction several methods have been developed to aid in selecting a network of biodiversity protected areas. one of these methods is artificial intelligence which includes a number of different computer algorithms that use an objective function to find the best solution. an algorithm is a mathematical process or a set of rules used for problem solving. recently, site selection algorithms hav...

Job Shop Scheduling Problem (JSSP) is an optimization problem in which ideal jobs are assigned to resources at particular times. In recent years many attempts have been made at the solution of JSSP using a various range of tools and techniques such as Branch and Bound and Heuristics algorithms. This paper proposed a new algorithm based on Genetic Algorithm (GA), Tabu Search (TS) and Simulated A...

We present a parallel computational environment used to determine conductivity properties of human head tissues when the effects of skull inhomogeneities are modeled. The environment employs a parallel simulated annealing algorithm to overcome poor convergence rates of the simplex method for larger numbers of head tissues required for accurate modeling of electromagnetic dynamics of brain funct...