ClickSoftware researchers contribute to new book on algorithms for vehicle routing - Click Software

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ClickSoftware researchers contribute to new book on algorithms for vehicle routing

September 23, 2008 ClickSoftware 0 Comments

A new book coming out in November 2008, “Bio-inspired Algorithms for the Vehicle Routing Problem”, includes nine chapters contributed by academic and industrial researchers. We are honored that the book’s editors chose to have one of these chapters authored by four people employed by, or associated with, ClickSoftware. The same people are also associated with several academic research institutes in the UK and in Israel.
The book’s publisher, Springer, includes it in the prestigious “Studies in Computational Intelligence” series, and describes the book as follows:

The vehicle routing problem (VRP) is one of the most famous combinatorial optimization problems. In simple terms, the goal is to determine a set of routes with overall minimum cost that can satisfy several geographical scattered demands. Biological inspired computation is a field devoted to the development of computational tools modeled after principles that exist in natural systems. The adoption of such design principles enables the production of problem solving techniques with enhanced robustness and flexibility, able to tackle complex optimization situations.

The goal of the volume is to present a collection of state-of-the-art contributions describing recent developments concerning the application of bio-inspired algorithms to the VRP. Over the 9 chapters, different algorithmic approaches are considered and a diverse set of problem variants are addressed. Some contributions focus on standard benchmarks widely adopted by the research community, while others address real-world situations.

The chapter contributed by ClickSoftware is titled “When the rubber meets the road: Bio-inspired field service scheduling in the real world”. It describes the complexity of business problems of field service scheduling, defines a framework for characterizing variants of such problems and supporting efficient solutions, describes some experimental algorithms which were developed and tested on top of this framework, and discusses some issues influencing the willingness of the workforce to accept automatically generated schedules and routes. These experimental algorithms involve adaptations of bio-inspired computer-science disciplines such as Genetic Algorithms and Ant Colony Optimization.

Copyright issues prevent us from posting a copy of the chapter on this blog. If you’re interested in discussing this further, please post a comment or contact ClickSoftware.

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