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Found 10 papers, 1 papers with code
Heuristic Search for Rank Aggregation with Application to Label Ranking
Rank aggregation aims to combine the preference rankings of a number of alternatives from different voters into a single consensus ranking.
Exploiting Local Optimality in Metaheuristic Search
A variety of strategies have been proposed for overcoming local optimality in metaheuristic search.
Bi-objective Optimization of Biclustering with Binary Data
This paper addresses a generalization called quasi-clustering that allows overlapping of clusters, and which we link to biclustering.
Quadratic Unconstrained Binary Optimization Problem Preprocessing: Theory and Empirical Analysis
The Quadratic Unconstrained Binary Optimization problem (QUBO) has become a unifying model for representing a wide range of combinatorial optimization problems, and for linking a variety of disciplines that face these problems.
Logical and Inequality Implications for Reducing the Size and Complexity of Quadratic Unconstrained Binary Optimization Problems
The quadratic unconstrained binary optimization (QUBO) problem arises in diverse optimization applications ranging from Ising spin problems to classical problems in graph theory and binary discrete optimization.
Memetic search for identifying critical nodes in sparse graphs
In this paper, we study the classic critical node problem (CNP) and introduce an effective memetic algorithm for solving CNP.
A History of Metaheuristics
This chapter describes the history of metaheuristics in five distinct periods, starting long before the first use of the term and ending a long time in the future.
Diversification-Based Learning in Computing and Optimization
Diversification-Based Learning (DBL) derives from a collection of principles and methods introduced in the field of metaheuristics that have broad applications in computing and optimization.
Diversification Methods for Zero-One Optimization
We introduce new diversification methods for zero-one optimization that significantly extend strategies previously introduced in the setting of metaheuristic search.
Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs
The bipartite boolean quadratic programming problem (BBQP) is a generalization of the well studied boolean quadratic programming problem.
