ABC Optimization: A Co-Operative Learning Approach to Complex Routing Problems

Many practical and complex problems in industry and business such as the routing problems, scheduling, networks design, telephone routing etc.,. are in the class of intractable combinatorial (discrete) or numerical (continuous or mixed) optimization problems. Many traditional methods were developed for solving continuous optimization problems, while discrete problems are being solved using heuristics. In the past few years, several modern metaheuristic algorithms that apply to both domains have been developed for solving such problems .They include population based, iterative based, stochastic, deterministic and other approaches. Classification can be made in two important groups of natural inspired and population based algorithms: evolutionary algorithms (EA) and swarm algorithms. The proposed method has been developed to detect and extract the best availability shortest traversal path for any complex routing problems. It uses an efficient Artificial Bee Colony algorithm based on the foraging behaviour of honey bees for solving numerical optimization problems.