Ant algorithms Review and future applications.pdfVIP

Ant Algorithms: Review and Future Applications Krishnan Krishnaiyer, S. Hossein Cheraghi Department of Industrial and Manufacturing Engineering Wichita State University Wichita, KS 67260-0035 Extended Abstract A search for a robust optimization methodology for addressing dynamic problems in business and engineering has been in research for the past decade. One such tool in the array of algorithms is the Ant algorithms, inspired by the behavior of the real ants. These algorithms fall in the category of search meta-heuristics, which are used to arrive at the best possible solution from an initial one. The natural ant colonies exhibit the application of adhoc and dynamic decision-making process in their day-to-day living activities such as foraging and brooding that can definitely be used as a tool to tackle the mercurial scenarios present in the current industrial and manufacturing environment. This paper presents an overview of the concept of Ant algorithms and provides a review of its applications to solve real world problems. Keywords Ant algorithms, meta-heuristics, search algorithm 1. Introduction The ever-increasing customer satisfaction and variety of products are making the business environment very dynamic. This changing market scene is making many industries to shuffle their manufacturing and distribution strategies and be focused on retaining the customers. A production schedule based on the last forecast is becoming impractical; allocation of resources and changing capacities are becoming more probabilistic. In these dynamic situations application of conventional operation research techniques is time consuming and there is a need for a heuristics that can provide an optimal or near optimal solution. To solve such practical combinatorial optimization problem, in the year 1986 Fred-Glover coined the term Meta-heuristics, which is basically oriented towards generating a global optimal solution for a given problem. Meta-heur