The Ncl Natural Constraint Language
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The NCL Natural Constraint Language
Author: Jianyang Zhou
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-09
"The NCL Natural Constraint Language" presents the NCL language which is a description language in conventional mathematical logic for modeling and solving constraint satisfaction problems. NCL differs from other declarative languages: It models problems naturally in a simplified form of first-order logic with quantifiers, Boolean logic, numeric constraints, set operations and logical functions; it solves problems by mixed set programming over the mixed domain of real numbers, integers, Booleans, dates/times, references, and in particular sets. The book uses plenty of examples and tutorials to illustrate NCL and its applications. It is intended for researchers and developers in the fields of logic programming, constraint programming, optimization, modeling, operations research and artificial intelligence, who will learn from a new programming language and theoretical foundations for industrial applications. Dr. Jianyang Zhou is the inventor of NCL and has worked for its industrialization for more than 10 years.
Dynamics in Logistics
This contributed volume brings together research papers presented at the 4th International Conference on Dynamics in Logistics, held in Bremen, Germany in February 2014. The conference focused on the identification, analysis and description of the dynamics of logistics processes and networks. Topics covered range from the modeling and planning of processes, to innovative methods like autonomous control and knowledge management, to the latest technologies provided by radio frequency identification, mobile communication, and networking. The growing dynamic poses wholly new challenges: logistics processes and networks must be(come) able to rapidly and flexibly adapt to constantly changing conditions. The book primarily addresses the needs of researchers and practitioners from the field of logistics, but will also be beneficial for graduate students.