We present two hybrid Metaheuristics, a hybrid Iterated Local Search and a hybrid Simulated Annealing, for solving real-world extensions of the Vehicle Routing Problem with Time Windows. Both hybrid Metaheuristics are based on the same neighborhood generating operators and local search procedures. The initial solutions are obtained by the Coefficient Weighted Distance Time Heuristics with autom...

Hybrid metaheuristics are powerful methods for solving complex problems in science and industry. Nevertheless, the resolution time remains prohibitive when dealing with large problem instances. As a result, the use of GPU computing has been recognized as a major way to speed up the search process. However, most GPU-accelerated algorithms of the literature do not take benefits of all the availab...

The emergence of metaheuristics for solving diÆcult combinatorial optimization problems is one of the most notable achievements of the last two decades in operations research. This paper provides an account of the most recent developments in the eld and identi es some common issues and trends. Examples of applications are also reported for vehicle routing and scheduling problems.

This paper proposes an adaptation of the RINS MIP heuristic which explicitly explores pre-processing techniques. The method systematically searches for the ideal number of fixations to produce subproblems of controlled size. These problems are explored in a Variable Neighborhood Descent fashion until a stopping criterion is met. Preliminary experiments implemented upon the open source MIP solve...

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Traditionally, supply chain planning problems consider variables with uncertainty associated with uncontrolled factors. These factors have been normally modelled by complex methodologies where the seeking solution process often presents high scale of difficulty. This work presents the fuzzy set theory as a tool to model uncertainty in supply chain planning problems and proposes the particle swa...

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This chapter describes the history of metaheuristics in five distinct periods, starting long before the first use of the term and ending a long time in the future.

In recent years, the field of combinatorial optimization has witnessed a true tsunami of “novel” metaheuristic methods, most of them based on a metaphor of some natural or man-made process. The behavior of virtually any species of insects, the flow of water, musicians playing together – it seems that no idea is too far-fetched to serve as inspiration to launch yet another metaheuristic. In this...