Algorithms for path optimizations: a short survey

• Published in: Computing Vol. 105; no. 2; pp. 293 - 319
• Main Authors: De Sirisuriya, S C M S, Fernando, T G I, Ariyaratne, M K A
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.02.2023; Springer Nature B.V
• Subjects: Academic disciplines; Algorithms; Artificial Intelligence; Computer Appl. in Administrative Data Processing; Computer Communication Networks; Computer Science; Generators; Genetic algorithms; Information Systems Applications (incl.Internet); Machine learning; Nature; Optimization; Optimization algorithms; Optimization techniques; Regular Paper; Robotics; Route optimization; Software Engineering; State-of-the-art reviews; Traveling salesman problem; Swarm Intelligence Algorithms; Evolutionary Algorithms; Machine Learning Algorithms; 68T07; Robotic Path Planing; Path Optimization; Vehicle Routing
• ISSN: 0010-485X; 1436-5057
• DOI: 10.1007/s00607-022-01126-w

Path finding is used to solve the problem of finding a traversable path through an environment with obstacles. This problem can be seen in many different fields of study and these areas rely on fast and efficient path finding algorithms. This paper aims to describe and review state of the art optimization techniques that are used on optimized path finding and compare their performances. Moreover, a special attention is paid on the proposed approaches to identify how they are tested on different test cases; whether the test cases are automatically generated or benchmark instances. The review opens avenues about the importance of automatic test case generation to test the different path finding algorithms.