This survey provides an overview of popular pathfinding algorithms and techniques based on graph generation problems. We focus on recent developments and improvements in existing techniques and examine their impact on robotics and the video games industry. We have categorized pathfinding algorithms based on a 2D/3D environment search. The aim of this paper is to provide researchers with a thorough background on the progress made in the last 10 years in this field, summarize the principal techniques, and describe their results. We also give our expectations for future trends in this field and discuss the possibility of using pathfinding techniques in more extensive areas.

Metabolic pathways have become increasingly available for various microorganisms. Such pathways have spurred the development of a wide array of computational tools, in particular, mathematical pathfinding approaches. This article can facilitate the understanding of computational analysis of metabolic pathways in genomics. Moreover, stoichiometric and pathfinding approaches in metabolic pathway analysis are discussed. Three major types of studies are elaborated: stoichiometric identification models, pathway-based graph analysis and pathfinding approaches in cellular metabolism. Furthermore, evaluation of the outcomes of the pathways with mathematical benchmarking metrics is provided. This review would lead to better comprehension of metabolism behaviors in living cells, in terms of computed pathfinding approaches.

No abstract

No abstract

There have been various pathfinding algorithms created and developed over the past few decades to assist in finding the best path between two points. This paper presents a comparison of several algorithms for pathfinding on 2D grid maps. As a result, this study identified Jump Point Search Block Based Jumping (JPS (B)) as a potential algorithm in term of five evaluation metrics including search time. The comparisons pointed out the potential algorithm and code optimization was performed on the selected JPS(B) algorithm, and it was named JPS(BCO). This paper also explores issues regarding the JPS(B) and how to resolve them in order to optimize access to the index pointer. The presented enhance JPS(BCO) is capable to search optimal path quicker than the original JPS(B) as demonstrated by experimental findings. An experiment of different size grid maps is conducted to validate the ability of the proposed algorithm in term of search time. The comparative study with original JPS (B) exhibits the enhancement that has more benefits on grid maps of different size in terms of search time.