A Hybrid Genetic Algorithm For Optimal Hexagonal Tortoise Problem

A Hybrid Genetic Algorithm for the Hexagonal Tortoise Problem

We propose a hybrid genetic algorithm for the hexagonal tortoise problem. We combined the genetic algorithm with an efficient local heuristic and aging mechanism. Another search heuristic which focuses on the space around existing solutions is also incorporated into the genetic algorithm. With the proposed algorithm, we could find the optimal solutions of up to a fairly large problem.

A Hybrid Geneti Algorithm for Optimal Hexagonal Tortoise Problem

An Evolutionary Algorithm Based on a Hybrid Multi-Attribute Decision Making Method for the Multi-Mode Multi-Skilled Resource-constrained Project Scheduling Problem

This paper addresses the multi-mode multi-skilled resource-constrained project scheduling problem. Activities of real world projects often require more than one skill to be accomplished. Besides, in many real-world situations, the resources are multi-skilled workforces. In presence of multi-skilled resources, it is required to determine the combination of workforces assigned to each activity. H...

A Hybrid Algorithm using Firefly, Genetic, and Local Search Algorithms

In this paper, a hybrid multi-objective algorithm consisting of features of genetic and firefly algorithms is presented. The algorithm starts with a set of fireflies (particles) that are randomly distributed in the solution space; these particles converge to the optimal solution of the problem during the evolutionary stages. Then, a local search plan is presented and implemented for searching s...

A novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and setup costs of large permutation flow-shop scheduling problems with sequence-dependent setup times on each machine, this pap...