Search Results for author:
Found 25 papers, 6 papers with code
A Three-Phase Search Approach for the Quadratic Minimum Spanning Tree Problem
Given an undirected graph with costs associated with each edge as well as each pair of edges, the quadratic minimum spanning tree problem (QMSTP) consists of determining a spanning tree of minimum total cost.
A Memetic Algorithm for the Linear Ordering Problem with Cumulative Costs
This paper introduces an effective memetic algorithm for the linear ordering problem with cumulative costs.
A Multi-parent Memetic Algorithm for the Linear Ordering Problem
In this paper, we present a multi-parent memetic algorithm (denoted by MPM) for solving the classic Linear Ordering Problem (LOP).
On memetic search for the max-mean dispersion problem
Computational experiments on the set of 160 benchmark instances with up to 1000 elements commonly used in the literature show that the proposed algorithm improves or matches the published best known results for all instances in a short computing time, with only one exception, while achieving a high success rate of 100\%.
Reinforcement learning based local search for grouping problems: A case study on graph coloring
Grouping problems aim to partition a set of items into multiple mutually disjoint subsets according to some specific criterion and constraints.
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.
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.
Combining tabu search and graph reduction to solve the maximum balanced biclique problem
The Maximum Balanced Biclique Problem is a well-known graph model with relevant applications in diverse domains.
Iterated two-phase local search for the Set-Union Knapsack Problem
The Set-union Knapsack Problem (SUKP) is a generalization of the popular 0-1 knapsack problem.
Population-based Gradient Descent Weight Learning for Graph Coloring Problems
Unlike existing methods for graph coloring that are specific to the considered problem, the presented work targets a generic objective by introducing a unified method that can be applied to different graph coloring problems.
Variable Population Memetic Search: A Case Study on the Critical Node Problem
Population-based memetic algorithms have been successfully applied to solve many difficult combinatorial problems.
Solving the Clustered Traveling Salesman Problem via TSP methods
The Clustered Traveling Salesman Problem (CTSP) is a variant of the popular Traveling Salesman Problem (TSP) arising from a number of real-life applications.
Probability Learning based Tabu Search for the Budgeted Maximum Coverage Problem
As the counterpart problem of SUKP, however, BMCP was introduced early in 1999 but since then it has been rarely studied, especially there is no practical algorithm proposed.
A threshold search based memetic algorithm for the disjunctively constrained knapsack problem
The disjunctively constrained knapsack problem consists in packing a subset of pairwisely compatible items in a capacity-constrained knapsack such that the total profit of the selected items is maximized while satisfying the knapsack capacity.
A massively parallel evolutionary algorithm for the partial Latin square extension problem
The partial Latin square extension problem is to fill as many as possible empty cells of a partially filled Latin square.
A deep learning guided memetic framework for graph coloring problems
Given an undirected graph $G=(V, E)$ with a set of vertices $V$ and a set of edges $E$, a graph coloring problem involves finding a partition of the vertices into different independent sets.
An effective hybrid search algorithm for the multiple traveling repairman problem with profits
As an extension of the traveling repairman problem with profits, the multiple traveling repairman problem with profits consists of multiple repairmen who visit a subset of all customers to maximize the revenues collected through the visited customers.
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.
On Monte Carlo Tree Search for Weighted Vertex Coloring
This work presents the first study of using the popular Monte Carlo Tree Search (MCTS) method combined with dedicated heuristics for solving the Weighted Vertex Coloring Problem.
Combining Monte Carlo Tree Search and Heuristic Search for Weighted Vertex Coloring
This work investigates the Monte Carlo Tree Search (MCTS) method combined with dedicated heuristics for solving the Weighted Vertex Coloring Problem.
Fast Maximum $k$-Plex Algorithms Parameterized by Small Degeneracy Gaps
We define a novel parameter of the input instance, $g_k(G)$, the gap between the degeneracy bound and the size of the maximum $k$-plex in the given graph, and present an exact algorithm parameterized by this $g_k(G)$, which has a worst-case running time polynomial in the size of the input graph and exponential in $g_k(G)$.
Deinterleaving of Discrete Renewal Process Mixtures with Application to Electronic Support Measures
In this paper, we propose a new deinterleaving method for mixtures of discrete renewal Markov chains.
A Multi-population Integrated Approach for Capacitated Location Routing
The capacitated location-routing problem involves determining the depots from a set of candidate capacitated depot locations and finding the required routes from the selected depots to serve a set of customers whereas minimizing a cost function that includes the cost of opening the chosen depots, the fixed utilization cost per vehicle used, and the total cost (distance) of the routes.
Learning-guided iterated local search for the minmax multiple traveling salesman problem
The minmax multiple traveling salesman problem involves minimizing the longest tour among a set of tours.
A reinforcement learning guided hybrid evolutionary algorithm for the latency location routing problem
The latency location routing problem integrates the facility location problem and the multi-depot cumulative capacitated vehicle routing problem.
