Titlebook: Integration of AI and OR Techniques in Constraint Programming; 13th International C Claude-Guy Quimper Conference proceedings 2016 Springer

正當理由

書目名稱Integration of AI and OR Techniques in Constraint Programming影響因子(影響力)




書目名稱Integration of AI and OR Techniques in Constraint Programming影響因子(影響力)學科排名




書目名稱Integration of AI and OR Techniques in Constraint Programming網(wǎng)絡公開度




書目名稱Integration of AI and OR Techniques in Constraint Programming網(wǎng)絡公開度學科排名




書目名稱Integration of AI and OR Techniques in Constraint Programming被引頻次




書目名稱Integration of AI and OR Techniques in Constraint Programming被引頻次學科排名




書目名稱Integration of AI and OR Techniques in Constraint Programming年度引用




書目名稱Integration of AI and OR Techniques in Constraint Programming年度引用學科排名




書目名稱Integration of AI and OR Techniques in Constraint Programming讀者反饋




書目名稱Integration of AI and OR Techniques in Constraint Programming讀者反饋學科排名

散布

Time-Series Constraints: Improvements and Application in CP and MIP Contexts,ence of values taken by the variables; such an automaton can also be used to decompose its specified constraint into a conjunction of logical constraints. The inference achieved by this decomposition in a CP solver can be boosted by automatically generated implied constraints on the accumulators, pr

TOXIN

Finding a Collection of MUSes Incrementally, different preferences over these .. Typical . systems produce a single . without much control over which . is generated. In this paper we describe an algorithm that can efficiently compute a collection of ., thus presenting an application with a range of choices. Our algorithm improves over previou

粗鄙的人

Decomposition Based on Decision Diagrams, classical benchmarks. This success is primarily driven by a DDs ability to capture structure. This paper exploits this characteristic and proposes a novel solution method which decomposes a problem into highly-structured portions, where the solution set of each portion can be compactly represented

嚴厲批評

IRS

Lagrangian Decomposition via Sub-problem Search,function can be inferred at each search node. The stronger the bound that can be inferred, the earlier failed subtrees can be detected, leading to an exponentially smaller search tree. Normal CP solvers are only capable of inferring a bound on the objective function via propagating the problem const

Cytokines

Non-linear Optimization of Business Models in the Electricity Market,iberalization is opening new perspectives. This calls for the development of methodologies and tools that energy providers can use to define specific business models. In this work we develop an optimization model to provide recommendations on time-of-use based prices to providers, taking into accoun

耐寒

Weighted Spanning Tree Constraint with Explanations,rld applications are usually subject to constraints that do not let us apply such methods directly. In these cases we confront a version of the MST called the “Weighted Spanning Tree” (WST) in which we look for a spanning tree in a graph that satisfies other side constraints and is of minimum cost.

Pituitary-Gland

Forward-Checking Filtering for Nested Cardinality Constraints: Application to an Energy Cost-Aware et paper, kitchen rolls, facial tissues) is such an industry. Its production process is flexible enough to leverage partial planning reorganization allowing to reduce electricity consumption. The idea is to shift the production of the tissues (rolls) requiring more energy when electricity prices (fo

amorphous