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1.

図書

図書
Pascal van Hentenryck (ed.)
出版情報: Berlin ; New York : Springer, c1997  x, 412 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 1302
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2.

図書

図書
edited by Pascal Van Hentenryck
出版情報: Cambridge, Mass. ; London : MIT Press, c1994  xx, 752 p. ; 23 cm
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3.

電子ブック

EB
Pascal Hentenryck, Takeo Kanade, Pascal Van Hentenryck
出版情報: Springer eBooks Computer Science , Springer Berlin / Heidelberg, 2006
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4.

電子ブック

EB
Pascal Hentenryck, David Hutchison, Takeo Kanade, Pascal Van Hentenryck, Laurence Wolsey, Laurence A. Wolsey
出版情報: Springer eBooks Computer Science , Springer Berlin Heidelberg, 2007
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5.

図書

図書
Pascal Van Hentenryck (ed.)
出版情報: Berlin ; Tokyo : Springer, c2002  xvi, 794 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2470
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6.

図書

図書
Pascal Van Hentenryck (ed.)
出版情報: Berlin : Springer, c2006  x, 229 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 3819
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7.

図書

図書
Pascal Van Hentenryck ; with contributions by Irvin Lustig, Laurent Michel, and Jean-Franc̦ois Puget
出版情報: Cambridge, Mass. : MIT Press, c1999  x, 245 p. ; 23 cm
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8.

図書

図書
Pascal Van Hentenryck, Laurent Michel
出版情報: Cambridge, Mass. : MIT Press, c2005  xix, 422 p. ; 24 cm.
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目次情報: 続きを見る
Preface
Local Search / I:
Neighborhood Search / 1:
Illustration / 1.1:
Formalization / 1.3:
Properties of Neighborhood / 1.4:
Heuristics and Metaheuristics / 2:
The Generic Local Search / 2.1:
Heuristics / 2.2:
Metaheuristics / 2.3:
Notes and Further Reading / 2.4:
Constraint-Based Local Search / II:
An Overview of the Architecture / 3:
The Architecture at Work / 3.2:
Modeling / 3.3:
Magic Squares / 4.1:
Send More Money / 4.2:
The Zebra Puzzle / 4.3:
Magic Series / 4.4:
All-Interval Series / 4.5:
Searching / 5:
The Queens'Problem / 5.1:
Comet / 5.2:
Invariants / 6:
Invariants at Work / 6.1:
Numerical Invariants / 6.2:
Set Invariants / 6.3:
Combinatorial Invariants / 6.4:
Implementation / 6.5:
Differentiable Objects / 6.6:
Constraints / 7.1:
Objectives / 7.2:
User-Defined Objectives / 7.3:
Objective Over Booleans / 7.4:
First-Class Expressions / 7.5:
Control / 7.6:
Selectors / 8.1:
Solutions / 8.2:
Atomicity / 8.3:
Simulation / 8.4:
First-Order Control / 8.5:
Enabling Technologies / 9.1:
Events / 9.2:
Neighbors / 9.3:
Checkpoints / 9.4:
Nondeterministic Search / 9.5:
Applications / 9.6:
Tabu Search / 10:
The Progressive Party / 10.1:
Car Sequencing / 10.2:
Graph Coloring / 10.3:
Warehouse Location / 10.4:
Variable Neighborhood Search / 11:
The k-Median Problem / 11.1:
The Model / 11.2:
The Search / 11.3:
Simulated Annealing / 11.4:
Experimental Results / 12.1:
Guided Local Search / 12.4:
Frequency Allocation / 13.1:
Frequency Minimization / 13.2:
Hybrid Evolutionary Search / 13.3:
An Implementation of Hybrid Evolutionary Search / 14.1:
Domain-Independent Local Search / 14.2:
Constraint-Directed Search / 15.1:
ACC Basketball Scheduling / 15.3:
Ant Colony Optimization / 15.4:
Scheduling / 16.1:
Jobshop Scheduling / 17:
Problem Specifications / 17.1:
Disjunctive Schedules / 17.2:
Critical Paths / 17.3:
Neighborhoods / 17.4:
Move Evaluation / 17.5:
Scheduling Abstractions / 18:
The Computational Model / 18.1:
Schedules and Activities / 18.2:
Jobs / 18.3:
Cumulative Resources / 18.4:
Precedence Constraints / 18.5:
Disjunctive Resources / 18.6:
Objective Functions / 18.7:
Minimizing Total Tardiness in a Jobshop / 18.8:
The Problem / 19.1:
Overview of the Algorithm / 19.2:
Overview of the Implementation / 19.3:
Minimizing Makespan in a Jobshop / 19.4:
The Tabu Scheme / 20.1:
Algorithm Behavior / 20.6:
Minimizing Makespan in a Jobshop Again / 20.8:
The Intensification Scheme / 21.1:
Cumulative Scheduling / 21.4:
The Search Procedure / 22.1:
References / 22.5:
Index
Heuristics and Mathematics
Preface
Local Search / I:
Neighborhood Search / 1:
9.

電子ブック

EB
Pascal Van Hentenryck and Russell Bent
出版情報: EBSCOhost  1 online resource (xiii, 232 p.)
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目次情報: 続きを見る
Preface
Introduction / 1:
From A Priori to Online Stochastic Optimization / 1.1:
Online Stochastic Combinatorial Optimization / 1.2:
Online Anticipatory Algorithms / 1.3:
Online Stochastic Combinatorial Optimization in Context / 1.4:
Organization and Themes / 1.5:
Online Stochastic Scheduling / I:
The Generic Offline Problem / 2:
The Online Problem / 2.2:
The Generic Online Algorithm / 2.3:
Properties of Online Stochastic Scheduling / 2.4:
Oblivious Algorithms / 2.5:
The Expectation Algorithm / 2.6:
The Consensus Algorithm / 2.7:
The Regret Algorithm / 2.8:
Immediate Decision Making / 2.9:
The Suboptimality Approximation Problem / 2.10:
Notes and Further Reading / 2.11:
Theoretical Analysis / 3:
Expected Loss / 3.1:
Local Errors / 3.2:
Bounding Local Errors / 3.3:
The Theoretical Results / 3.4:
Discussion on the Theoretical Assumptions / 3.5:
Packet Scheduling / 3.6:
The Packet Scheduling Problem / 4.1:
The Optimization Algorithm / 4.2:
The Greedy Algorithm is Competitive / 4.3:
The Suboptimality Approximation / 4.4:
Experimental Setting / 4.5:
Experimental Results / 4.6:
The Anticipativity Assumption / 4.7:
Online Stochastic Reservations / 4.8:
The Offline Reservation Problem / 5:
Cancellations / 5.2:
Online Multiknapsack Problems / 6:
Online Multiknapsack with Deadlines / 6.1:
Online Stochastic Routing / 6.2:
Vehicle Routing with Time Windows / 7:
Vehicle Dispatching and Routing / 7.1:
Large Neighborhood Search / 7.2:
Online Stochastic Vehicle Routing / 7.3:
Online Single Vehicle Routing / 8.2:
Service Guarantees / 8.3:
A Waiting Strategy / 8.4:
A Relocation Strategy / 8.5:
Multiple Pointwise Decisions / 8.6:
Online Vehicle Dispatching / 8.7:
The Online Vehicle Dispatching Problems / 9.1:
Setting of the Algorithms / 9.2:
Visualizations of the Algorithms / 9.3:
Online Vehicle Routing with Time Windows / 9.5:
The Online Instances / 10.1:
Learning and Historical Sampling / 10.2:
Learning Distributions / 11:
The Learning Framework / 11.1:
Hidden Markov Models / 11.2:
Learning Hidden Markov Models / 11.3:
Historical Sampling / 11.4:
Historical Averaging / 12.1:
Sequential Decision Making / 12.2:
Markov Chance-Decision Processes / 13:
Motivation / 13.1:
Decision-Chance versus Chance-Decision / 13.2:
Equivalence of MDCPs and MCDPs / 13.3:
The Approximation Theorem for Anticipative MCDPs / 13.4:
Beyond Anticipativity / 13.6:
The General Approximation Theorem for MCDPs / 13.8:
References / 13.9:
Index
Preface
Introduction / 1:
From A Priori to Online Stochastic Optimization / 1.1:
10.

電子ブック

EB
Pascal Van Hentenryck, Pascal Van Hentenryck
出版情報: SpringerLink Books - AutoHoldings , Springer Berlin Heidelberg, 1997
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