A Comparison between Harris and FAST - Corner Detection of Noisy Images Using Adaptive Non-Local Means

Hussein, Ahmed Abdulmunem

doi:10.24237/djps.1304.307a

Cited by 1 publication

(1 citation statement)

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“…Sometimes, that knowledge can be used to help solve problems that are similar to ones that have already been solved, which is known as transfer learning [121]. The decomposition of the search space or data is another application for applying a variety of applications [122]. By separating the data into smaller sub-spaces, decomposition has a nontrivial role in reducing the computing cost of the process and facilitating the generation of better first solutions [123].…”

Section: Initial Solutionmentioning

confidence: 99%

Learnheuristics in routing and scheduling problems: A review

Hussein¹,

Yaseen²,

Rashid³

2023

sjpas

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Combinatorial optimization problems (COPs) are the most important class of optimization problems, with great practical significance. This class is concerned with identifying the best solution from a discrete set of all available options. The transportation (routing) and distribution (scheduling) systems are considered the most challenging optimization examples of the COPs. Given the importance of routing and scheduling problems, many methods have been proposed to address them. These methods can be categorized into traditional (exact and metaheuristics (MHs) methods) and machine learning (ML) methods. ML methods have been proposed to overcome the problems that traditional methods suffer from, especially high computational time and dependence on the knowledge of experts. Recently, ML methods and MHs have been combined to tackle the COPs, and then the learnheuristics term emerged. This combination aims to guide the MHs toward an efficient, effective, and robust search and improve their performance in terms of solution quality. This work reviews the publications in which the collaboration between MHs and ML has been utilized to propose a guideline for the researchers to put forward new algorithms that have a good ability to solve routing and scheduling problems.

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Section: Initial Solutionmentioning

confidence: 99%