this paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. first, the problem is formulated as a mixed integer linear programming model. then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. two experiments are carried out to evaluate th...

⎯ Optimization of complex systems has been for many years limited to problems that could be formulated as mathematical programming models of linear, nonlinear and integer types. Problemspecific heuristics that do not require a mathematical formulation of the problem have been also used for optimizing complex systems, however, they generally must be developed in a case-by-case basis. Recent rese...

Metaheuristics are effective strategies for solving optimization problems. However, when trying to solve an instance of this kind of problems it is hard to know which algorithm should be used. Hybrid systems provide flexible tools that can help to cope with this problem. Therefore a hybrid system based on the intelligent combination of different strategies will give more robustness and will all...

This paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the fuzzyclustering problem, especially for large sizes. When the problem becomes large, theFCM algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. The PSO algorithm does find ago...

One of the new emerging application strategies for optimization is the hybridization of existing metaheuristics. The research combines the unique paradigms of solution space sampling of SOMA and memory retention capabilities of Scatter Search for the task of capacitated vehicle routing problem. The new hybrid heuristic is tested on the Taillard sets and obtains good results.

Metaheuristics have received considerable interest these recent years in the field of combinatorial optimization. However, the choice of a particular algorithm to optimize a certain problem is still mainly driven by some sort of devotion of its author to a certain technique rather than by a rationalistic choice driven by reason. Hybrid algorithms have shown their ability to provide local optima...

Metaheuristics are a class of effective algorithms for optimization problems. A basic implementation of a metaheuristic typically requires rather little development effort. With a significantly larger investment in the design, implementation, and fine-tuning, metaheuristics can often produce state-of-the-art results. According to the amount of development effort, we say that an implementation o...

in this paper, we consider the fuzzy fixed-charge transportation problem (ffctp). both of fixed and transportation cost are fuzzy numbers. contrary to previous works, electromagnetism-like algorithms (em) is firstly proposed in this research area to solve the problem. three types of em; original em, revised em, and hybrid em are firstly employed for the given problem. the latter is being firstl...