A New Hybrid Routing Algorithm based on Genetic and Simulated Annealing for Vehicular Ad hoc Networks

This paper presents a new heuristic algorithm for the graph coloring problem based on a combination of genetic algorithms and simulated annealing. Our algorithm exploits a novel crossover operator for graph coloring. Moreover, we investigate various ways in which simulated annealing can be used to enhance the performance of an evolutionary algorithm. Experiments performed on various collections...

nowadays, one-dimensional cutting stock problem (1d-csp) is used in many industrial processes and re-cently has been considered as one of the most important research topic. in this paper, a metaheuristic algo-rithm based on the simulated annealing (sa) method is represented to minimize the trim loss and also to fo-cus the trim loss on the minimum number of large objects. in this method, the 1d-...

Flexible job shop scheduling problem (FJSP) is one of the hardest combinatorial optimization problems known to be NP-hard. This paper proposes a novel hybrid imperialist competitive algorithm with simulated annealing (HICASA) for solving the FJSP. HICASA explores the search space by using imperial competitive algorithm (ICA) and use a simulated annealing (SA) algorithm for exploitation in the s...

In this paper, we demonstrate the ease in which an adaptive simulated annealing algorithm can be designed. Specifically, we use the adaptive annealing schedule known as the modified Lam schedule to apply simulated annealing to the weighted tardiness scheduling problem with sequence-dependent setups. The modified Lam annealing schedule adjusts the temperature to track the theoretical optimal rat...

The Economic Lot Scheduling Problem (ELSP) has been well-researched for more than 40 years. As the ELSP has been generally seen as NP-hard, researchers have focused on the development of efficient heuristic approaches. In this paper, we consider the time-varying lot size approach to solve the ELSP. A computational study of the existing solution algorithms, Dobson’s heuristic, Hybrid Genetic alg...

This paper deals with modeling and optimization of the roll-bonding process of Ti/Cu/Ti composite for determination of the best roll-bonding parameters leading to the maximum Ti/Cu bond strength by combination of neural network and genetic algorithm. An artificial neural network (ANN) program has been proposed to determine the effect of practical parameters, i.e., rolling temperature, reduction...