Titlebook: Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problem; 8th International Co Tobias Achterber

公理

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/468824.jpg

GIDDY

共和國

Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problem978-3-642-21311-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

使長胖

內(nèi)閣

Enzyme

Preference Elicitation and Preference Learning in Social Choice,ch preference data from user populations can now be elicited, assessed, or estimated in online settings. In many domains, the preferences of a group of individuals must be aggregated to form a single consensus recommendation, placing us squarely in the realm of social choice.

大約冬季

Propagation in Constraints: How One Thing Leads to Another,n, for example similar search methods, heuristics, and learning techniques. So what is it that is essentially different about Constraint Programming in particular? One answer is the power and diversity of constraint propagation algorithms. By contrast, other search disciplines often rely on just one

變形

On Bilevel Programming and Its Impact in Branching, Cutting and Complexity, interested in this talk is to discuss the bilevel nature of two of the most crucial ingredients of enumerative methods for solving combinatorial optimization problems, namely . and ...Specifically, we discuss a new branching method for 0-1 programs called . [3] that exploits the intrinsic bilevel n

NAV

中止

Manipulating MDD Relaxations for Combinatorial Optimization, relaxations are used for the purpose of generating lower bounds. We introduce a new compilation method for constructing such MDDs, as well as algorithms that manipulate the MDDs to obtain stronger relaxations and hence provide stronger lower bounds. We apply our methodology to set covering problems