A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects
AE Ezugwu, AM Ikotun, OO Oyelade… - … Applications of Artificial …, 2022 - Elsevier
Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …
active research in many fields of study, such as computer science, data science, statistics …
Optimization problems for machine learning: A survey
This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …
framework several commonly used machine learning approaches. Particularly …
Variable neighborhood search: basics and variants
Variable neighborhood search (VNS) is a framework for building heuristics, based upon
systematic changes of neighborhoods both in a descent phase, to find a local minimum, and …
systematic changes of neighborhoods both in a descent phase, to find a local minimum, and …
The dial-a-ride problem with electric vehicles and battery swapping stations
Abstract The Dial-a-Ride Problem (DARP) consists of designing vehicle routes and
schedules for customers with special needs and/or disabilities. The DARP with Electric …
schedules for customers with special needs and/or disabilities. The DARP with Electric …
Optimization of product category allocation in multiple warehouses to minimize splitting of online supermarket customer orders
In an online supermarket, people may purchase multiple items in a single order for
convenience or to obtain free delivery. Multi-item customer orders often need to be split into …
convenience or to obtain free delivery. Multi-item customer orders often need to be split into …
Dominant-set clustering: A review
Clustering refers to the process of extracting maximally coherent groups from a set of objects
using pairwise, or high-order, similarities. Traditional approaches to this problem are based …
using pairwise, or high-order, similarities. Traditional approaches to this problem are based …
A general variable neighborhood search for solving the uncapacitated -allocation -hub median problem
The p p-hub median problem consists of choosing pp hub locations from a set of nodes with
pairwise traffic demands in order to route the traffic between the origin-destination pairs at …
pairwise traffic demands in order to route the traffic between the origin-destination pairs at …
Nested general variable neighborhood search for the periodic maintenance problem
R Todosijević, R Benmansour, S Hanafi… - European Journal of …, 2016 - Elsevier
In this paper we study the periodic maintenance problem: given a set of m machines and a
horizon of T periods, find indefinitely repeating itself maintenance schedule such that at most …
horizon of T periods, find indefinitely repeating itself maintenance schedule such that at most …
Ascent–descent variable neighborhood decomposition search for community detection by modularity maximization
In this paper we propose a new variant of the Variable Neighborhood Decomposition
Search (VNDS) heuristic for solving global optimization problems. We call it Ascent-Descent …
Search (VNDS) heuristic for solving global optimization problems. We call it Ascent-Descent …
Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems
O Janković, S Mišković, Z Stanimirović… - Annals of Operations …, 2017 - Springer
This paper deals with uncapacitated single and multiple allocation p-hub maximal covering
problems (USApHMCP and UMApHMCP) with binary and partial covering criteria. We …
problems (USApHMCP and UMApHMCP) with binary and partial covering criteria. We …