A Tree-Based Heuristic for the One-Dimensional Cutting Stock Problem Optimization Using Leftovers.

Cutting problems consist of cutting a set of objects available in stock in order to produce the desired items in specified quantities and sizes. The cutting process can generate leftovers (which can be reused in the case of new demand) or losses (which are discarded). This paper presents a tree-based heuristic method for minimizing the number of cut bars in the one-dimensional cutting process, satisfying the item demand in an unlimited bar quantity of just one type.

Letter on the results of the BASiNET method in the paper 'A systematic evaluation of computational tools for lncRNA identification'.

This letter points out a conceptual error made by the authors of a published paper, which presents a review and evaluation of computational methods in lncRNA identification. The error was made in the execution of the BASiNET method when considering an example file (toy model) made available by the authors with the aim of showing how a classification model could be stored in a file for later use. In this letter, this error is contextualized, the correct use of the BASiNET method is pointed out and the results of its correct execution to one of the datasets used in the review article are presented.