Vital nodes identification in complex networks

Personnel scheduling: A literature review

Real networks exhibit heterogeneous nature with nodes playing far different roles in structure and function. To identify vital nodes is thus very significant, allowing us to control the outbreak of epidemics, to conduct advertisements for e-commercial products, to predict popular scientific publications, and so on. The vital nodes identification attracts increasing attentions from both computer science and physical societies, with algorithms ranging from simply counting the immediate neighbors to complicated machine learning and message passing approaches. In this review, we clarify the concepts and metrics, classify the problems and methods, as well as review the important progresses and describe the state of the art. Furthermore, we provide extensive empirical analyses to compare well-known methods on disparate real networks, and highlight the future directions. In despite of the emphasis on physics-rooted approaches, the unification of the language and comparison with cross-domain methods would trigger interdisciplinary solutions in the near future.

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We present an exact partial enumerative algorithm for the maximum clique problem. The pruning device used is derived from graph colorings. Pruning of the search tree is accomplished not only by the number of colors used to color a tree subproblem but also by using information gained in the process of coloring. This leads to increased pruning which translates into improved computational performance. Experimental results on test problems are presented.

An exact algorithm for the maximum clique problem with accelerated pruning

The third comprehensive survey on scheduling problems with setup times/costs

In recent years the unconstrained binary quadratic program (UBQP) has grown in importance in the field of combinatorial optimization due to its application potential and its computational challenge. Research on UBQP has generated a wide range of solution techniques for this basic model that encompasses a rich collection of problem types. In this paper we survey the literature on this important model, providing an overview of the applications and solution methods.

/pdf/the-unconstrained-binary-quadratic-programming-problem-a-42pv0mgvaf.pdf

The unconstrained binary quadratic programming problem: a survey

http://www.info.univ-angers.fr/pub/hao/papers/EJOR09.pdf

A Memetic Algorithm for Graph Coloring

http://www.info.univ-angers.fr/pub/hao/papers/EJOR08.pdf

Adaptive Tabu Search for course timetabling

Path relinking for unconstrained binary quadratic programming

This paper describes a Diversification-Driven Tabu Search (D2TS) algorithm for solving unconstrained binary quadratic problems. D2TS is distinguished by the introduction of a perturbation-based diversification strategy guided by long-term memory. The performance of the proposed algorithm is assessed on the largest instances from the ORLIB library (up to 2500 variables) as well as still larger instances from the literature (up to 7000 variables). The computational results show that D2TS is highly competitive in terms of both solution quality and computational efficiency relative to some of the best performing heuristics in the literature.

/pdf/diversification-driven-tabu-search-for-unconstrained-binary-2qrk07z2rd.pdf

Zhipeng Lü

Papers

The unconstrained binary quadratic programming problem: a survey

A Memetic Algorithm for Graph Coloring

Adaptive Tabu Search for course timetabling

Path relinking for unconstrained binary quadratic programming

Diversification-driven tabu search for unconstrained binary quadratic problems