For solving traveling salesman problem (TSP), the ant colony optimization (ACO) algorithm and simulated annealing (SA) algorithm are used to propose a two-phase hybrid optimization (TPASHO) algorithm in this paper. In proposed TPASHO algorithm, the advantages of parallel, collaborative and positive feedback of the ACO algorithm are used to implement the global search in the current temperature....

The Probabilistic Traveling Salesman Problem (PTSP) is a variation of the well known Traveling Salesman Problem (TSP). This problem arises when the information about customers demand is not available at the moment of the tour generation and/or the tour re-calculating cost is too elevated. In this article, a Hybrid Algorithm combining Particle Swarm Optimization (PSO) and Simulated Annealing (SA...

The sandwich algorithm (SA) is an alternative to the data augmentation (DA) algorithm that uses an extra simulation step at each iteration. In this paper, we show that the sandwich algorithm always converges at least as fast as the DA algorithm, in the Markov operator norm sense. We also establish conditions under which the spectrum of SA dominates that of DA. An example illustrates the results.

this paper aims to investigate the integrated production/distribution and inventory planning for perishable products with fixed life time in the constant condition of storage throughout a two-echelon supply chain by integrating producers and distributors. this problem arises from real environment in which multi-plant with multi-function lines produce multi-perishable products with fixed life ti...

In this paper, a hybrid algorithm of binary lightning search algorithm and simulated annealing (BLSA-SA) is proposed to optimize the design of multilayer microwave absorbers for normal incidence. The multilayer absorber is designed to find a set of coatings that minimize the reflection coefficient over the desired frequency. The design problem is translated into solving the binary problem. Thre...

—Community detection is one of the most important issues in complex networks. In this paper, integrating Infomap and Simulated Annealing (SA) algorithm, and based on the thought of optimizationof the modularity function, the authors are proposing a novel algorithm Infomap-SA for detecting community. In order to verify the accuracy and efficiency of this algorithm, the performance of this algor...

The Graph k-Colorability Problem (GCP) is a well known NP-hard problem which consist in finding the k minimum number of colors to paint the vertices of a graph in such a way that any two vertices joined by an edge have always different colors. Many years ago, Simulated Annealing (SA) was used for graph coloring task obtaining good results; however SA is not a complete algorithm and it not alway...

The problem of influence maximization, i.e., mining top-k influential nodes from a social network such that the spread of influence in the network is maximized, is NP-hard. Most of the existing algorithms for the problem are based on greedy algorithm. Although greedy algorithm can achieve a good approximation, it is computational expensive. In this paper, we propose a totally different approach...

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA), is introduced and referred to as APSO-SA. This algorithm uses a novel PSO algorithm (APSO) to increase the convergence rate and...

Sea port container terminals play an important role in the national and regional economy. The integrated scheduling of handling equipment has been recently investigated in literature to improve the performance of the container terminals. In this paper, an integrated scheduling of quay cranes and automated guided vehicles is formulated as a mixed integer linear programming model. This model mini...