標(biāo)題: Titlebook: Decision Diagrams for Optimization; David Bergman,Andre A. Cire,John Hooker Book 2016 The Editor(s) (if applicable) and The Author(s), und [打印本頁(yè)] 作者: CLAST 時(shí)間: 2025-3-21 17:01
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書目名稱Decision Diagrams for Optimization讀者反饋
書目名稱Decision Diagrams for Optimization讀者反饋學(xué)科排名
作者: MUT 時(shí)間: 2025-3-21 22:20 作者: DRAFT 時(shí)間: 2025-3-22 02:27 作者: 圣人 時(shí)間: 2025-3-22 06:01 作者: conceal 時(shí)間: 2025-3-22 11:11 作者: 信任 時(shí)間: 2025-3-22 13:04
https://doi.org/10.1007/978-1-4615-0286-9 models can be used in a top-down compilation method to construct exact decision diagrams. We also present an alternative compilation method based on constraint separation. We illustrate our framework on a number of classical combinatorial optimization problems: maximum independent set, set covering作者: 信任 時(shí)間: 2025-3-22 19:33 作者: Silent-Ischemia 時(shí)間: 2025-3-22 23:28
Data Mining and Knowledge Discovery Handbookd diagram can be perceived as a counterpart of the concept of relaxed diagrams introduced in previous chapters, and represents an under approximation of the feasible set, the objective function, or both. We first show how to modify the top-down compilation approach to generate restricted diagrams th作者: Offbeat 時(shí)間: 2025-3-23 05:01 作者: 等待 時(shí)間: 2025-3-23 08:31
Dimension Reduction and Feature Selectionpact of variable ordering on the size of exact decision diagrams for the maximum independent set problem. We provide worst-case bounds on the size of the exact decision diagram for particular classes of graphs. For general graphs, we show that the size is bounded by the Fibonacci numbers. Lastly, we作者: choleretic 時(shí)間: 2025-3-23 10:01 作者: Blasphemy 時(shí)間: 2025-3-23 14:16 作者: Abutment 時(shí)間: 2025-3-23 20:53
https://doi.org/10.1007/978-1-4419-0522-2employee rostering and car manufacturing. It will serve to illustrate the main challenges when studying MDD propagation for a new constraint type: Tractability, design of the propagation algorithm, and practical efficiency. In particular, we show in this chapter that establishing MDD consistency for作者: dithiolethione 時(shí)間: 2025-3-23 23:49
https://doi.org/10.1007/978-1-4419-0522-2 provide exact and relaxed MDD representations, together with MDD filtering algorithms for various side constraints, including time windows, precedence constraints, and sequence-dependent setup times. We extend a constraint-based scheduling solver with these techniques, and provide an experimental e作者: 枕墊 時(shí)間: 2025-3-24 02:48
David Bergman,Andre A. Cire,John HookerPresents a new theoretical and algorithmic approach to discrete optimization.Authors among leading researchers in this domain.Useful for researchers and practitioners in discrete optimization and cons作者: 熔巖 時(shí)間: 2025-3-24 09:00
Artificial Intelligence: Foundations, Theory, and Algorithmshttp://image.papertrans.cn/d/image/264187.jpg作者: 激勵(lì) 時(shí)間: 2025-3-24 14:22 作者: IRK 時(shí)間: 2025-3-24 15:47 作者: 真實(shí)的你 時(shí)間: 2025-3-24 22:13 作者: 拖網(wǎng) 時(shí)間: 2025-3-25 00:28
https://doi.org/10.1007/978-1-4615-0286-9constraint separation. We illustrate our framework on a number of classical combinatorial optimization problems: maximum independent set, set covering, set packing, single machine scheduling, maximum cut, and maximum 2-satisfiability.作者: Diatribe 時(shí)間: 2025-3-25 04:03 作者: sphincter 時(shí)間: 2025-3-25 08:59 作者: ANTE 時(shí)間: 2025-3-25 14:58 作者: Ceremony 時(shí)間: 2025-3-25 18:17
Introduction,onstraint propagation, primal heuristics, and intelligent modeling. It presents a simple example to illustrate how decision diagrams can be used to solve an optimization problem. It concludes with a brief outline of the book.作者: 神刊 時(shí)間: 2025-3-25 22:34
Exact Decision Diagrams,constraint separation. We illustrate our framework on a number of classical combinatorial optimization problems: maximum independent set, set covering, set packing, single machine scheduling, maximum cut, and maximum 2-satisfiability.作者: Hippocampus 時(shí)間: 2025-3-26 01:43
Restricted Decision Diagrams,of the feasible set, the objective function, or both. We first show how to modify the top-down compilation approach to generate restricted diagrams that observe an input-specified width. Next, we provide a computational study of the bound provided by restricted diagrams, particularly focusing on the set covering and set packing problems.作者: 來(lái)這真柔軟 時(shí)間: 2025-3-26 06:13
Variable Ordering,the exact decision diagram for particular classes of graphs. For general graphs, we show that the size is bounded by the Fibonacci numbers. Lastly, we demonstrate experimentally that variable orderings that produce small exact decision diagrams also produce better bounds from relaxed decision diagrams.作者: 里程碑 時(shí)間: 2025-3-26 09:25 作者: 收到 時(shí)間: 2025-3-26 13:58 作者: 步履蹣跚 時(shí)間: 2025-3-26 18:51
Dimension Reduction and Feature Selectionombinatorial optimization problems, and compare our solution technology with mixed-integer linear programming. Finally, we conclude by showing how the diagram-based branch-and-bound procedure is suitable for ., and provide empirical evidence of almost linear speedups on the maximum independent set problem.作者: 嘲笑 時(shí)間: 2025-3-26 23:08 作者: Chameleon 時(shí)間: 2025-3-27 04:02 作者: 全等 時(shí)間: 2025-3-27 07:33
https://doi.org/10.1007/978-1-4419-0522-2valuation for a wide range of problems, including the traveling salesman problem with time windows, the sequential ordering problem, and minimum-tardiness sequencing problems. The results demonstrate that MDD propagation can improve a state-of-the-art constraint based scheduler by orders of magnitude in terms of solving time.作者: CT-angiography 時(shí)間: 2025-3-27 11:25 作者: deadlock 時(shí)間: 2025-3-27 16:01 作者: 淡紫色花 時(shí)間: 2025-3-27 19:09
Recursive Modeling,tate-dependent costs with canonical arc costs in a decision diagram, a technique that can sometimes greatly simplify the recursion, as illustrated by a textbook inventory management problem. It concludes with an extension to nonserial recursive modeling and nonserial decision diagrams.作者: 免除責(zé)任 時(shí)間: 2025-3-27 22:32
MDD Propagation for , Constraints, . is NP-hard, but fixed-parameter tractable. Furthermore, we present an MDD propagation algorithm that may not establish MDD consistency, but is highly effective in practice when compared to conventional domain propagation.作者: 退潮 時(shí)間: 2025-3-28 03:35 作者: temperate 時(shí)間: 2025-3-28 06:51 作者: Deadpan 時(shí)間: 2025-3-28 10:34
Data Mining and Decision Support for the maximum independent set problem. The chapter concludes by describing an alternative method to generate relaxed diagrams, the ., and exemplify its application to a single-machine makespan problem.作者: 前奏曲 時(shí)間: 2025-3-28 15:36 作者: Obvious 時(shí)間: 2025-3-28 21:57
Book 2016ments over state-of-the-art technology. The authors present chapters on the use of decision diagrams for combinatorial optimization and constraint programming, with attention to general-purpose solution methods as well as problem-specific techniques...The book will be useful for researchers and prac作者: 悶熱 時(shí)間: 2025-3-29 00:21
Introduction,agrams implement the five main solution strategies of general-purpose optimization and constraint programming methods: relaxation, branching search, constraint propagation, primal heuristics, and intelligent modeling. It presents a simple example to illustrate how decision diagrams can be used to so作者: configuration 時(shí)間: 2025-3-29 06:31
Historical Overview,amming. It begins with an early history of decision diagrams and their relation to switching circuits. It then surveys some of the key articles that brought decision diagrams into optimization and constraint solving. In particular it describes the development of relaxed and restricted decision diagr作者: miracle 時(shí)間: 2025-3-29 10:17
Exact Decision Diagrams, models can be used in a top-down compilation method to construct exact decision diagrams. We also present an alternative compilation method based on constraint separation. We illustrate our framework on a number of classical combinatorial optimization problems: maximum independent set, set covering作者: 使尷尬 時(shí)間: 2025-3-29 14:06 作者: OASIS 時(shí)間: 2025-3-29 19:34
Restricted Decision Diagrams,d diagram can be perceived as a counterpart of the concept of relaxed diagrams introduced in previous chapters, and represents an under approximation of the feasible set, the objective function, or both. We first show how to modify the top-down compilation approach to generate restricted diagrams th作者: 相反放置 時(shí)間: 2025-3-29 20:23
Branch-and-Bound Based on Decision Diagrams,ristics used in general-purpose optimization techniques. In particular, we show an enumeration scheme that branches on the . of a relaxed decision diagram, as opposed to variable-value assignments as in traditional branch-and-bound. We provide a computational study of our method on three classical c
