Coalitional Stability in Matching Problems with Externalities and Random Preferences

2021 ◽  
Author(s):  
Adriana Piazza ◽  
Juan Pablo Torres-Martínez
Keyword(s):  
Matching Problems ◽  
Coalitional Stability

Coalitional stability and efficiency of partitions in matching problems

2010 ◽  
Vol 71 (3) ◽  
pp. 395-407 ◽  
Author(s):  
Duygu Nizamogullari ◽  
İpek Özkal-Sanver
Keyword(s):  
Matching Problems ◽  
Coalitional Stability

When Prudent Behavior Immobilizes: Asymptotic Stability in Matching Problems With Externalities

2019 ◽  
Author(s):  
Milton dos Santos Braitt ◽  
Juan Pablo Torres-Martínez
Keyword(s):  
Asymptotic Stability ◽  
Matching Problems

scholarly journals On the unification of the graph edit distance and graph matching problems

2021 ◽  
Vol 145 ◽  
pp. 240-246
Author(s):  
Romain Raveaux
Keyword(s):  
Edit Distance ◽  
Graph Matching ◽  
Graph Edit Distance ◽  
Matching Problems

scholarly journals Entropy-Based Approach in Selection Exact String-Matching Algorithms

Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 31
Author(s):  
Ivan Markić ◽  
Maja Štula ◽  
Marija Zorić ◽  
Darko Stipaničev
Keyword(s):  
String Matching ◽  
Quantitative Measure ◽  
Search Pattern ◽  
Maximum Efficiency ◽  
Resource Usage ◽  
Specific Domain ◽  
Matching Problems ◽  
Algorithm Efficiency ◽  
Testing Algorithm ◽  
Algorithm Implementation

The string-matching paradigm is applied in every computer science and science branch in general. The existence of a plethora of string-matching algorithms makes it hard to choose the best one for any particular case. Expressing, measuring, and testing algorithm efficiency is a challenging task with many potential pitfalls. Algorithm efficiency can be measured based on the usage of different resources. In software engineering, algorithmic productivity is a property of an algorithm execution identified with the computational resources the algorithm consumes. Resource usage in algorithm execution could be determined, and for maximum efficiency, the goal is to minimize resource usage. Guided by the fact that standard measures of algorithm efficiency, such as execution time, directly depend on the number of executed actions. Without touching the problematics of computer power consumption or memory, which also depends on the algorithm type and the techniques used in algorithm development, we have developed a methodology which enables the researchers to choose an efficient algorithm for a specific domain. String searching algorithms efficiency is usually observed independently from the domain texts being searched. This research paper aims to present the idea that algorithm efficiency depends on the properties of searched string and properties of the texts being searched, accompanied by the theoretical analysis of the proposed approach. In the proposed methodology, algorithm efficiency is expressed through character comparison count metrics. The character comparison count metrics is a formal quantitative measure independent of algorithm implementation subtleties and computer platform differences. The model is developed for a particular problem domain by using appropriate domain data (patterns and texts) and provides for a specific domain the ranking of algorithms according to the patterns’ entropy. The proposed approach is limited to on-line exact string-matching problems based on information entropy for a search pattern. Meticulous empirical testing depicts the methodology implementation and purports soundness of the methodology.

Improved Analytic Starting Points for Beam Matching Problems to Be Solved on Digital Computers

1979 ◽  
Vol 26 (3) ◽  
pp. 3505-3507 ◽  
Author(s):  
Philip F. Meads
Keyword(s):  
Matching Problems ◽  
Digital Computers

scholarly journals Designing Random Allocation Mechanisms: Theory and Applications

2013 ◽  
Vol 103 (2) ◽  
pp. 585-623 ◽  
Author(s):  
Eric Budish ◽  
Yeon-Koo Che ◽  
Fuhito Kojima ◽  
Paul Milgrom
Keyword(s):  
Resource Allocation ◽  
School Choice ◽  
Real World ◽  
Random Allocation ◽  
Assignment Problems ◽  
Matching Problems ◽  
House Allocation ◽  
Controlled Choice ◽  
Ex Post ◽  
Ex Ante

Randomization is commonplace in everyday resource allocation. We generalize the theory of randomized assignment to accommodate multi-unit allocations and various real-world constraints, such as group-specific quotas (“controlled choice”) in school choice and house allocation, and scheduling and curriculum constraints in course allocation. We develop new mechanisms that are ex ante efficient and fair in these environments, and that incorporate certain non-additive substitutable preferences. We also develop a “utility guarantee” technique that limits ex post unfairness in random allocations, supplementing the ex ante fairness promoted by randomization. This can be applied to multi-unit assignment problems and certain two-sided matching problems. (JEL C78, D82)

An incompatibility between recursive unanimity and strategy-proofness in two-sided matching problems

2011 ◽  
Vol 40 (2) ◽  
pp. 461-478 ◽  
Author(s):  
Takumi Kongo
Keyword(s):  
Matching Problems ◽  
Strategy Proofness

Beam Matching Problems concerning the Axial Injection System for the Karlsruhe Cyclotron

1971 ◽  
Vol 18 (3) ◽  
pp. 321-325 ◽  
Author(s):  
W. P. Lutter ◽  
F. Schild ◽  
H. M. Thimmel ◽  
P. Wucherer
Keyword(s):  
Injection System ◽  
Axial Injection ◽  
Matching Problems
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