Simulation optimization (SO) refers to the optimization of an objective function subject to
constraints, both of which can be evaluated through a stochastic simulation. To address …

Portfolio optimization is the process of determining the best combination of securities and
proportions with the aim of having less risk and obtaining more profit in an investment …

Distributed permutation flowshop scheduling problem (DPFSP) has become a very active
research area in recent years. However, minimizing total flowtime in DPFSP, a very relevant …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

The field of metaheuristics for the application to combinatorial optimization problems is a
rapidly growing field of research. This is due to the importance of combinatorial optimization …

Memetic computing is a subject in computer science which considers complex structures
such as the combination of simple agents and memes, whose evolutionary interactions lead …

A History of Metaheuristics arxiv:1704.00853v1 [cs.AI] 4 Apr 2017 Page 1 A History of
Metaheuristics ∗ Kenneth Sörensen Marc Sevaux Fred Glover Abstract This chapter …

Owing to the no free lunch theorem, no single optimisation algorithm can solve all
optimisation problems accurately, so new optimisation techniques are required. In this …

The current state of the art in hyper-heuristic research comprises a set of approaches that
share the common goal of automating the design and adaptation of heuristic methods to …

GRASP is a multi-start metaheuristic for combinatorial optimization problems, in which each
iteration consists basically of two phases: construction and local search. The construction …