This chapter introduces and overviews an emerging methodology in search and optimisation. One of the key aims of these new approaches, which have been termed hyper-heuristics, is to raise the level of generality at which optimisation systems can operate. An objective is that hyper-heuristics will lead to more general systems that are able to handle a wide range of problem domains rather than cu...

The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Evolutionary computation and swarm intelligence meta-heuristics are outstanding examples that nature has been an unending source of inspiration. The behaviour of bees, bacteria, glow-worms, fireflies, slime moulds, cockroaches, mosquitoes and other organisms have insp...

This paper presents a new mathematical programming model for the bi-criteria mixed-model assembly line balancing problem in a just-in-time (JIT) production system. There is a set of criteria to judge sequences of the product mix in terms of the effective utilization of the system. The primary goal of this model is to minimize the setup cost and the stoppage assembly line cost, simultaneously. B...

As a small energy system, microgrid plays an important role in utilizing distributed resources, improving traditional networks, and building intelligent integrated systems. However, management is always challenging optimization problem due to different factors. Meta-heuristics have been widely used solve complex problems many fields, including there lack of systematic summary the application me...

A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The lea...

Numerous multistage planning problems in finance involve nonlinear and nonconvex decision controls. One of the simplest is the fixed-mix • Research supported in part by NSF grant CCR-9102660 and Air Force grant AFOSR-91-0359. We acknowledge the assistance of Michael T. Tapia in preparing this paper for publication. investment strategy. At each stage during the planning horizon, an in· vestor re...

Many efficient meta-heuristics were developed to solve the vehicle routing problem (VRP). However, these heuristics often require large computation times and significant effort to implement. In this paper we propose a simple and efficient heuristic that only uses the Clarke and Wright’s savings heuristic, the 2-opt and the 3-opt improvement heuristics. It will be shown that the proposed heurist...

Meta-heuristic algorithms are applied in optimization problems in a variety of fields, including engineering, economics, and computer science. In this paper, seven population-based meta-heuristic algorithms are employed for size and geometry optimization of truss structures. These algorithms consist of the Artificial Bee Colony algorithm, Cyclical Parthenogenesis Algorithm, Cuckoo Search algori...

In this paper we prove that in some practical situations, there is a free lunch for hyper-heuristics, i.e., search algorithms that search the space of solvers, searchers, meta-heuristics and heuristics for problems.