Software System for Container Vessel Stowage Planning using Genetic Algorithm

Author(s):  
Miri Weiss Cohen ◽  
Adi Dahan ◽  
Izzik Kaspi
Author(s):  
N. KHARMA ◽  
T. KOWALIW ◽  
E. CLEMENT ◽  
C. JENSEN ◽  
A. YOUSSEF ◽  
...  

We describe the desire for a black box approach to pattern classification: a generic Autonomous Pattern Recognizer, which is capable of self-adapting to specific alphabets without human intervention. The CellNet software system is introduced, an evolutionary system that optimizes a set of pattern-recognizing agents relative to a provided set of features and a given pattern database. CellNet utilizes a new genetic operator designed to facilitate a canalization of development: Merger. CellNet utilizes our own set of arbitrarily chosen features, and is applied to the CEDAR Database of handwritten Latin characters, as well as to a database of handwritten Indian digits provided by CENPARMI. CellNet's cooperative co-evolutionary approach shows significant improvement over a more standard Genetic Algorithm, both in terms of efficiency and in nearly eliminating over-fitting (to the training set). Additionally, the binary classifiers autonomously evolved by CellNet return validation accuracies approaching 98% for both Latin and Indian digits, with no global changes to the system between the two trials.


2018 ◽  
Vol 65 ◽  
pp. 495-516 ◽  
Author(s):  
Anibal Tavares Azevedo ◽  
Luiz Leduino de Salles Neto ◽  
Antônio Augusto Chaves ◽  
Antônio Carlos Moretti

Procedia CIRP ◽  
2015 ◽  
Vol 36 ◽  
pp. 17-22 ◽  
Author(s):  
Miri Weiss Cohen ◽  
Michael Aga ◽  
Tomer Weinberg

2021 ◽  
Author(s):  
Andrei Corezolla ◽  
Lincoln Costa ◽  
Francisco Carlos Souza ◽  
Alinne Correa Souza

It can be challenging for people to select the most relevant requirementamong several software system development options.Requirements prioritization defines the ordering for executing requirementsbased on their priority or importance concerning stakeholders’viewpoints, which is a problematic task. Based on thisproblem, this study aims to present a requirements prioritizationapproach using a genetic algorithm to find optimal solutions, andit can assist in the requirements prioritization activity during thesoftware development process. In this paper, we investigated aset of criteria to create four functions GUT-D, ThS-D, ST, and LT,to assess candidate solutions, i.e., the recommended prioritizedrequirements. We examine the empirical results concerning thepractical approach’s effectiveness and cost computational two experimentsin the evaluation. We found that the 𝐺𝑈𝑇 − 𝐷 fitnessfunction achieved the best fitness value in different settings with90.51% and 98.63%. Besides that, our study demonstrates that the approachis promising to assist requirements prioritization since eachfitness function can be used individually according to companies’necessities.


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