Metaheuristics like ant colony optimization (ACO) can be used to solve combinatorial optimization problems. In this paper we refer on its successful application to the vehicle routing problem (VRP). At the beginning, we introduce the VRP and some of its variants. The variants of VRP were designed to reproduce the kind of situations faced in the real-world. Further, we introduce the fundamentals of ant colony optimization, and we present in few words its application to the solution of the VRP. At the end, we discuss the applications of ACO to a number of real-world problems: a VRP with time windows for a major supermarket chain in Switzerland; a VRP with pickup and delivery for a leading distribution company in Italy and an on-line VRP in the city of Lugano, Switzerland, where clients’ orders arrive during the delivery process.

EURONEWS (http://www.euronews.net), the multilingual European TV channel, reports that scientists in Lugano, Switzerland have been developing a way to optimise the movement of a fleet of trucks to make delivery services more efficient. Their unlikely source of inspiration has been the master of logistics in the natural world- the ant.
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A single ant or bee isn't smart, but their colonies are. The study of swarm intelligence is providing insights that can help humans manage complex systems, from truck routing to military robots.

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With AntRoute AntOptima implements this technology for Logistics provider to speed up their business in terms of time and efficiency. The integrated high performance Tour Optimiser of AntRoute based on ACO and is automatically able to optimise thousands of daily orders in a few minutes considering the company related constraints like truck fleet, client time windows, unit load, access limitation, etc. (Published on Logforum.net)

IDSIA, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale is a research institute active in both theoretical and applied research in the field of Operations Research and Artificial Intelligence. Since 1996 IDSIA has capitalized on the results obtained in the theoretical field applying them to real world logistics and transport application.

"For years, scientists have been studying ants, bees, and wasps because of the amazing efficiency of social insect. Now companies like Southwest Airlines and Unilever are actually putting that research to work, with impressive paybacks".

"Research in social insect behaviour has provided computer scientists with powerful methods for designing distributed control and optimization algorithms. These techniques are being applied successfully to a variety of scientific and engineering problems. In addition to achieving good performance on a wide spectrum of "static" problems, such techniques tend to exhibit a high degree of flexibility and robustness in a dynamic environment".

“The Flexible Job Shop Problem is an extension of the classical job shop scheduling problem which allows an operation to be performed by one machine out of a set of machines. The problem is to assign each operation to a machine (routing problem) and to order the operations on the machines (sequencing problem), such that the maximal completion time (makespan) of all operations is minimized. To solve the Flexible Job Shop problem approximately, we use local search techniques and present two neighborhood functions”.