Faced with the challenge of solving hard optimization problems that abound in the real
world, classical methods often encounter serious difficulties. Important applications in …

The objective of single row facility layout problem (SRFLP) is to assemble a full permutation
of facilities along a straight line so that the weighted sum of pairwise distances is minimized …

The CO2 emission of transportation is significantly reduced by the employment of green
vehicles to the existing vehicle fleet of the organizations. This paper intends to optimize the …

Neural Combinatorial Optimization attempts to learn good heuristics for solving a set of
problems using Neural Network models and Reinforcement Learning. Recently, its good …

Global random search algorithms are characterized by using probability distributions to
optimize problems. Among them, generative methods iteratively update the distributions by …

Abstract The Linear Ordering Problem (LOP) is a very popular NP-hard combinatorial
optimization problem with many practical applications that may require the use of large …

The linear ordering problem (LOP) is a difficult permutation-based optimization task with a
multitude of practical applications in different areas. The objective of the LOP is to maximize …

Recent advances in graph neural network (GNN) architectures and increased computation
power have revolutionized the field of combinatorial optimization (CO). Among the proposed …

A number of local search based algorithms have been designed to escape from the local
optima, such as, iterated local search or variable neighborhood search. The neighborhood …

Gradient search is a classical technique for optimizing differentiable functions that has
gained much relevance recently due to its application on Neural Network training. Despite …