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Journal ArticleDOI

Random assignment problems

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TLDR
This paper presents an overview of the recent results and developments in the area of probabilistic assignment problems, including the linear and multidimensional assignments problems, quadratic assignment problem, etc.
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This article is published in European Journal of Operational Research.The article was published on 2009-04-01. It has received 60 citations till now. The article focuses on the topics: Quadratic assignment problem & Generalized assignment problem.

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Citations
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Proceedings ArticleDOI

Local Optima Networks of the Quadratic Assignment Problem

TL;DR: In this paper, the authors conducted a thorough analysis of two types of instances of the Quadratic Assignment Problem (QAP) and found that real-like instances are easier to solve exactly using heuristic search, while uniform instances are easy to solve approximately.
Journal ArticleDOI

Fully Distributed Optimal Channel Assignment for Open Spectrum Access

TL;DR: This paper introduces a modified auction algorithm that can be applied in a fully distributed way using an opportunistic CSMA assignment scheme and is ε optimal, and shows that, in the case of i.i.d. Rayleigh channels, a simple greedy scheme is asymptotically optimal as SNR increases or as the number of users is increased to infinity.
Journal ArticleDOI

A survey on human resource allocation problem and its applications

TL;DR: The main resolution approaches: exact, heuristic and metaheuristics methods proposed to solve the human resource allocation problem are studied and the different contributions examined are discussed and analyzed.
Journal ArticleDOI

Connectivity and bandwidth-aware real-time exploration in mobile robot networks

TL;DR: Connectivity and bandwidth-aware exploration (CBAX) is proposed, which is an efficient iteration based real-time exploration that outperforms two recent exploration schemes qualitatively by demonstrating major improvement in terms of non-overflow transmission time and fully connected transmission time.
Journal ArticleDOI

Analyzing the Sensitivity of the Optimal Assignment in Probabilistic Multi-Robot Task Allocation

TL;DR: This work describes a parameterizable variant of the assignment problem that enables a designer to express preferences, allowing one to take a risk-averse position if the problem demands it, and introduces algorithms that provide an interval for the preference parameter in which all values result in the same optimal assignment.
References
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Journal ArticleDOI

The Hungarian method for the assignment problem

TL;DR: This paper has always been one of my favorite children, combining as it does elements of the duality of linear programming and combinatorial tools from graph theory, and it may be of some interest to tell the story of its origin this article.
Book ChapterDOI

Reducibility Among Combinatorial Problems

TL;DR: The work of Dantzig, Fulkerson, Hoffman, Edmonds, Lawler and other pioneers on network flows, matching and matroids acquainted me with the elegant and efficient algorithms that were sometimes possible.

Reducibility Among Combinatorial Problems.

TL;DR: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held, which made me aware of the importance of distinction between polynomial-time and superpolynomial-time solvability.
Journal ArticleDOI

Spin Glass Theory and Beyond

TL;DR: In this paper, a detailed and self-contained presentation of the replica theory of infinite range spin glasses is presented, paying particular attention to new applications in the study of optimization theory and neural networks.
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