A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. O...

In this paper, three simulated annealing based algorithms that exploit auxiliary knowledge in different ways are devised and employed to handle a manufacturing process planning problem for reconfigurable manufacturing. These algorithms are configured based on a generic combination of the simulated annealing technique with; (a) heuristic knowledge, and (b) metaknowledge. Capabilities of the impl...

With increasing interest in human-computer interaction, emotion recognition is becoming a hot spot. Support vector machine(SVM) is a machine learning algorithm based on statistic learning theory, finding the optimal separating hyperplane in the high dimensional feature space, having good classification and generalization ability. According to SVM method becoming very difficult for large data sc...

An important stage in circuit design is placement where components are assigned to physical locations on a chip A popular contemporary method for placement is the use of simulated annealing While this approach has been shown to produce good placement solutions recent work in genetic algorithms has produced promising results The purpose of this study is to determine which approach will result in...

in this paper, a multi-product continues review inventory control problem within batch arrival queuing approach (mqr/m/1) is modeled to find the optimal quantities of maximum inventory. the objective function is to minimize summation of ordering, holding and shortage costs under warehouse space, service level, and expected lost-sales shortage cost constraints from retailer and warehouse viewpoi...

This paper proposes a new algorithm of a simulated annealing (SA): Parallel Simulated Annealing using Genetic Crossover (PSA/GAc). The proposed algorithm consists of several processes, and in each process SA is operated. The genetic crossover is used to exchange information between solutions at fixed intervals. While SA requires high computational costs, particularly in continuous problems, thi...

The problem of multiprocessor scheduling can be stated as scheduling a general task graph on a multiprocessor system such that a set of performance criteria will be optimized. This study investigates the use of near optimal scheduling strategies in multiprocessor scheduling problem. The multiprocessor scheduling problem is modeled and simulated using five different simulated annealing algorithm...

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization pro...

This paper presents a novel dynamic Jellyfish Search Algorithm using Simulated Annealing and disruption operator, called DJSD. The developed DJSD method incorporates the operators into conventional in exploration stage, competitive manner, to enhance its ability discover more feasible regions. combination is performed dynamically fluctuating parameter that represents characteristics of hammer. ...