Multicriteria Evolutionary Weather Routing Algorithm in Practice | Zendy

Joanna Szłapczyńska | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Multicriteria Evolutionary Weather Routing Algorithm in Practice

Author(s) -

Joanna Szłapczyńska

Publication year - 2013

Publication title -

transnav the international journal on marine navigation and safety of sea transportation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.253

H-Index - 5

eISSN - 2083-6481

pISSN - 2083-6473

DOI - 10.12716/1001.07.01.07

Subject(s) - computer science , multi objective optimization , pareto principle , focus (optics) , mathematical optimization , topsis , ranking (information retrieval) , routing (electronic design automation) , operations research , evolutionary algorithm , fuzzy logic , industrial engineering , artificial intelligence , mathematics , engineering , machine learning , physics , optics , computer network

The Multicriteria Evolutionary Weather Routing Algorithm (MEWRA) has already been introduced by the author on earlier TransNav 2009 and 2011 conferences with a focus on theoretical application to a hybrid-propulsion or motor-driven ship. This paper addresses the topic of possible practical weather routing applications of MEWRA. In the paper some practical advantages of utilizing Pareto front as a result of multicriteria optimization in case of route finding are described. The paper describes the notion of Pareto-optimality of routes along with a simplified, easy to follow example. It also discusses a choice of the most suitable ranking method for MEWRA (a comparison between Fuzzy TOPSIS and Zero Unitarization Method is presented). In addition to that the paper briefly outlines a commercial application of MEWRA.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research