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Riders on a swarm

Mimicking the behaviour of ants, bees and birds started as a poor man’s version of artificial intelligence. It may, though, be the key to the real thing

The Economist, 2010 (PDF 123 Kb)
Ant Colony Optimization for Real-World Vehicle Routing

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.

SIGEVOlution Summer 2007
EURONEWS: Ants show the way in improving freight transport

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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National Geographic July 2007 - Swarm Behavior

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.

Link to article

July 2007
LOGFORUM.net - December 2006: AntRoute – Large scale dynamic optimisation

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)

LOGFORUM.NET – 2006, Vol.2, Issue 3, Nr. 4
IDSIA - January 2002: "Metaheuristics for Transport and Logistic"

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.

IDSIA 01/02 (PDF 106Kb)
Harvard Business Review - May 2001:

What do ants and bees have to do with business? A great deal, it turns out. Individually, social insects are only minimally intelligent, and their work together is largely self-organized and unsupervised. Yet collectively they're capable of finding highly efficient solutions to difficult problems and can adapt automatically to changing environments. Over the past 20 years, the authors and other researchers have developed rigorous mathematical models to describe this phenomenon, which has been dubbed "swarm intelligence," and they are now applying them to business. Their research has already helped several companies develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy. Emulating the way ants find the shortest path to a new food supply, for example, has led researchers at Hewlett-Packard to develop software programs that can find the most efficient way to route phone traffic over a telecommunications network. Southwest Airlines has used a similar model to efficiently route cargo. To allocate labor, honeybees appear to follow one simple but powerful rule--they seem to specialize in a particular activity unless they perceive an important need to perform another function. Using that model, researchers at Northwestern University have devised a system for painting trucks that can automatically adapt to changing conditions. In the future, the authors speculate, a company might structure its entire business using the principles of swarm intelligence. The result, they believe, would be the ultimate self-organizing enterprise--one that could adapt quickly and instinctively to fast-changing markets.

Link to the paper

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Nature - 6 July 2000: "Inspiration for optimization from social insect behaviour"

"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".

Nature 07/00 (PDF 148Kb)
Journal of Scheduling - January 2000: "Effective Neighborhood Functions for the Flexible Job Shop Problem"

“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”.

Journal of Scheduling 01/00 (PDF 413Kb)
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