Purpose This research aims to outline the key factors responsible for industry 4.0 (I4. 0)
application in industries and establish a factor stratification model. Design/methodology …

In recent years, the one-dimensional bin packing problem (1D-BPP) has become one of the
most famous combinatorial optimization problems. The 1D-BPP is a robust NP-hard problem …

Evolutionary algorithms have been reported to be efficient metaheuristics for the
optimization of several NP-Hard combinatorial optimization problems. In addition to their …

We propose a novel technique for algorithm-selection, applicable to optimisation domains in
which there is implicit sequential information encapsulated in the data, eg, in online bin …

The well-known one-dimensional Bin Packing Problem (BPP) of whose variants arise in
many real life situations is a challenging NP-Hard combinatorial optimization problem …

In this article, a multi-objective evolutionary framework to build selection hyper-heuristics for
solving instances of the 2D bin packing problem is presented. The approach consists of a …

We propose a novel technique for algorithm-selection which adopts a deep-learning
approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN …

In hierarchical production planning, the consideration of interdependencies between
superior top-level decisions and subordinate base-level decisions is essential. In this …

The paper investigates the two-dimensional irregular packing problem with multiple
homogeneous bins (2DIBPP). The literature on irregular shaped packing problems is …

Nature-inspired metaheuristic algorithms have steadily gained popularity over the last two
decades. They have been applied to a plethora of optimization problems both in continuous …