aPaRT: A Fast Meta-Heuristic Algorithm using Path-Relinking and Tabu Search for Allocating Machines to Operations in FJSP Problem

This paper proposes a multi-start local search algorithm that solves the flexible job-shop scheduling (FJSP) problem to minimize makespan. The proposed algorithm uses a path-relinking method to generate near optimal solutions. A heuristic parameter, $\alpha$, is used to assign machines to operations. Also, a tabu list is applied to avoid getting stuck at local optimums. The proposed algorithm is tested on two sets of benchmark problems (BRdata and Kacem) to make a comparison with the variable neighborhood search. The experimental results show that the proposed algorithm can produce promising solution in a shorter amount of time

Numerical and Evolutionary Optimization 2020

This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications