Mary E. Kurz

TL;DR: This paper examines scheduling in flexible flow lines with sequence-dependent setup times to minimize makespan, and finds an application of the Random Keys Genetic Algorithm to be very effective for the problems examined.

TL;DR: This paper explores scheduling flexible flow lines with sequence-dependent setup times with three major types of heuristics, and results indicate the range of conditions under which each method performs well.

TL;DR: In this article, the authors focus on the most enduring heuristics for the traveling salesman problem with an unrestricted distance matrix and differentiate between constructive heuristic which create feasible solutions from no solution, and improvement heuristic, which potentially create new feasible solution from existing feasible solutions.

TL;DR: This work addresses scheduling in parallel machines with sequence dependent set-up times and possibly non-zero ready times with the goal of minimizing makespan.

TL;DR: This paper proposes a methodology to find weakly Pareto optimal solutions to a symmetric multi-objective traveling salesman problem using a memetic random-key genetic algorithm that has been augmented by a 2-opt local search.