Ant Colony Optimization and Constraint Programming (Hardcover)

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts.

The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search approaches and metaheuristics, and shows how they can be integrated within constraint programming languages.

The second part describes the ant colony optimization metaheuristic and illustrates its capabilities on different constraint satisfaction problems.
The third part shows how the ant colony may be integrated within a constraint programming language, thus combining the expressive power of constraint programming languages, to describe problems in a declarative way, and the solving power of ant colony optimization to efficiently solve these problems.

螞蟻群體優化是一種元啟發式方法，已成功應用於各種組合優化問題。作者描述了這種元啟發式方法並研究了其在解決一些困難的組合問題上的效率，特別關注約束編程。該文本分為三個部分。

第一部分介紹了約束編程，它提供了高級功能，通過約束來聲明性地建模問題。它描述了解決約束滿足問題的主要現有方法，包括完整樹搜索方法和元啟發式方法，並展示了它們如何在約束編程語言中集成。

第二部分描述了螞蟻群體優化元啟發式方法，並展示了它在不同約束滿足問題上的能力。

第三部分展示了如何將螞蟻群體優化方法集成到約束編程語言中，從而結合了約束編程語言的表達能力，以聲明性的方式描述問題，以及螞蟻群體優化的求解能力，高效地解決這些問題。