the network design problem (ndp) is one of the important problems in combinatorial optimization. among the network design problems, the multicommodity capacitated network design (mcnd) problem has numerous applications in transportation, logistics, telecommunication, and production systems. the mcnd problems with splittable flow variables are np-hard, which means they require exponential time t...

This paper introduces and analyzes a parallel method of simulated annealing. Borrowing from genetic algorithms, an eeective combination of simulated annealing and genetic algorithms, called parallel recombinative simulated annealing, is developed. This new algorithm strives to retain the desirable asymptotic convergence properties of simulated annealing, while adding the populations approach an...

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show the relations between essential components in complex systems. In this paper, a novel learning method is proposed to construct FCMs based on historical data and by using meta-heuristic: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). Implementation of the proposed method has demonstrat...

An improved particle swarm optimization algorithm, which combines the idea of simulated annealing algorithm and opposition-based learning strategy, is presented for NP-hard protein structure prediction based on AB model. Flying grain is used to control the neighborhood structure of particle, so particle can search the global optimum in solution space more finely. An opposition-based learning is...

this paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. this paper presen...

considering the increasingly high attention to quality, promoting the reliability of products during designing process has gained significant importance. in this study, we consider one of the current models of the reliability science and propose a non-linear programming model for redundancy allocation in the series-parallel systems according to the redundancy strategy and considering the assump...

Nowadays, there are many optimization problems where exact methods do not exist or where deterministic methods are computationally too complex to implement. Simulated annealing may be the answer for these cases. It is not greedy in the sense that it is not fool with false minima, and is pretty easy to implement. Furthermore, because it does not require a mathematical model, it can be used to so...

Harmony search is a new heuristic optimization algorithm. Comparing with other algorithms, this algorithm has very strong robustness and can be easily operated. Combining with the features of harmony search, an improved simulated annealing algorithm is proposed in this paper. It can improve the speed of annealing. The initial state of simulated annealing and new solutions are generated by harmo...

In this paper, we present a simulated annealing (SA) and a genetic algorithm (GA) based on heuristics for scheduling problem of jobs in virtual cellular manufacturing systems. A virtual manufacturing cell (VMC) is a group of resources that is dedicated to the manufacturing of a part family. Although this grouping is not reflected in the physical structure of the manufacturing system, but machin...

The Network Design Problem (NDP) is one of the important problems in combinatorial optimization. Among the network design problems, the Multicommodity Capacitated Network Design (MCND) problem has numerous applications in transportation, logistics, telecommunication, and production systems. The MCND problems with splittable flow variables are NP-hard, which means they require exponential time t...