In this paper a complex scheduling problem in flexible manufacturing system (FMS) has been addressed with a novel approach called knowledge based genetic algorithm (KBGA). The literature review indicates that meta-heuristics may be used for combinatorial decision-making problem in FMS and simple genetic algorithm (SGA) is one of the meta-heuristics that has attracted many researchers. This nove...

In this paper, we study a resource-constrained project scheduling problem in which a set of project activities have due dates. If the finish time of each one of these activities is not equal to its due date, an earliness or a tardiness cost exists for each tardy or early period. The objective is to minimize the sum of discounted weighted earliness-tardiness penalty costs of these activities. Sc...

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...

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...

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.

Deterring the optimum design of large-scale structures is a difficult task. Great number of design variables, largeness of the search space and controlling great number of design constraints are major preventive factors in performing optimum design of large-scale truss structures in a reasonable time. Meta-heuristic algorithms are known as one of the useful tools to deal with these problems. Th...

Recently, the scheduling problem in distributed data-intensive computing environments has been an active research topic. This Chapter models the scheduling problem for work-flow applications in distributed dataintensive computing environments (FDSP) and makes an attempt to formulate the problem. Several meta-heuristics inspired from particle swarm optimization algorithm are proposed to formulat...

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...

Assembly sequence planning (ASP) plays an important role in intelligent manufacturing. As ASP is a non-deterministic polynomial (NP) hard problem, it is scarcely possible for a brute force approach to find out the optimal solution. Therefore, increasing meta-heuristic algorithms are introduced to solve the ASP problem. However, due to the discreteness and strong constraints of ASP problem, most...

We present a new genetic algorithm for playing the game of Mastermind. The algorithm requires low running times and results in a low expected number of guesses. Its performance is comparable to that of other meta-heuristics for the standard setting with four positions and six colors, while it outperforms the existing algorithms when more colors and positions are examined. The central idea under...