Magdalene Marinaki

TL;DR: The evolution of each individual of the total population, which consists of the parents and the offspring, is realized with the use of a Particle Swarm Optimizer where each has to improve its physical movement following the basic principles of Particles Swarm Optimization until it will obtain the requirements to be selected as a parent.

TL;DR: The proposed algorithm for the solution of the vehicle routing problem, the hybrid particle swarm optimization (HybPSO), combines a particle swarm optimized algorithm, the multiple phase neighborhood search-greedy randomized adaptive search procedure (MPNS-GRASP), the expanding neighborhood search (ENS) strategy and a path relinking (PR) strategy.

TL;DR: A new hybrid algorithmic nature inspired approach based on Particle Swarm Optimization (PSO), Greedy Randomized Adaptive Search Procedure (GRASP) and Expanding Neighborhood Search (ENS) Strategy is proposed for the solution of the PTSP.

TL;DR: This paper introduces a new hybrid algorithmic approach based on Particle Swarm Optimization (PSO) for successfully solving one of the most popular supply chain management problems, the Vehicle Routing Problem with Stochastic Demands (VRPSD).

TL;DR: In this study, an evolutionary approach, based on the differential evolution algorithm, is proposed in the context of the ELECTRE TRI method, to elicit the necessary preferential information from assignment examples.