Optimal multistage expansion of medium-voltage power network because of load growth is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints, make it a combinatorial problem which should be solved by optimization algorithms. In this paper, a new improved hybrid Tabu Search/ Particle Swarm Optimization algorithm is proposed...

This paper proposes a novel evolutionary optimization technique referred to the flower pollination algorithm (FPA) for system identification. The optimal parameters of an unknown infinite impulse response (IIR) system are computed using FPA. This algorithm is inspired by the pollination process of flowers. Proper tuning of control parameter has been performed in order to accomplish a balance be...

Ant colony optimization (ACO) and its variants are applied extensively to resolve various continuous optimization problems. As per the various diversification and intensification schemes of ACO for continuous function optimization, researchers generally consider components of multidimensional state space to generate the new search point(s). However, diversifying to a new search space by updatin...

Nowadays, in global free market, third-party logistics providers (3PLs) are becoming increasingly important. Hence, this study aims to develop the freight consolidation and containerization problem, which consists of loading items into containers and then shipping these containers to different warehouse they are delivered to their final destinations. In order to handle the proposed problem, thi...

Ant System algorithms are nature-inspired population-based metaheuristics derived from the field of swarm intelligence. Seemingly, the ant system has a lack of search diversity control since it has only a global pheromone update that intensifies the search. Hence, one or more assistant mechanisms are required to strengthen the search of the ant system. Therefore, we propose, in this study, an e...

Swarm intelligence is the technological modeling of behaviors of social insects, such as the ant or the honeybee. Although each element comprising swarm intelligence is simple, high grade intelligence emerges when the elements gather to form a swarm. Ant Colony Optimization (Dorigo, M, et al., 1997), which is called ACO, is one of the swarm intelligence and has been attracting much attention re...

This paper presents a new multi-objective hybrid model that makes cooperation between the strength of research of neighborhood methods presented by the tabu search (TS) and the important exploration capacity of evolutionary algorithm. This model was implemented and tested in benchmark functions (ZDT1, ZDT2, and ZDT3), using a network of computers. KeywordsMetaheuristics; hybrid method; intensif...

In nature-inspired metaheuristic algorithms, two key components are local intensification and global diversification, and their interaction can significantly affect the efficiency of a metaheuristic algorithm. However, there is no rule for how to balance these important components. In this paper, we provide a first attempt to give some theoretical basis for the optimal balance of exploitation a...

This paper presents a probabilistic technique to diversify, intensify and parallelize a local search adapted for solving vehicle routing problems. This technique may be applied to a very wide variety of vehicle routing problems and local searches. It is shown that efficient first level taboo searches for vehicle routing problems may be significantly improved with this technique. Moreover, the s...

In this paper we briefly describe Novelty and Adaptive Novelty, two high-performance, stochastic local search (SLS) algorithms for SAT. Based on the WalkSAT architecture, these algorithms combine search intensification and diversification feautures that lead to good peformance on a broad range of SAT instances. The performance of the Novelty algorithm critically depends on the setting of a soca...