Meta-heuristic algorithms should be compared using the best parameter values for all the involved algorithms. However, this is often unrealised despite the existence of several parameter tuning approaches. In order to further popularise tuning, this paper introduces a new tuning method CRS-Tuning that is based on meta-evolution and our novel method for comparing and ranking evolutionary algorit...

Unit commitment (UC) problem tries to schedule output power of generation units to meet the system demand for the next several hours at minimum cost. UC adds a time dimension to the economic dispatch problem with the additional choice of turning generators to be on or off.  In this paper, in order to improve both the exploitation and exploration abilities of the firefly algorithm (FA), a new mo...

This paper proposes a hybrid heuristic aiming the reduction of the average bandwidth of sparse matrices. The proposed heuristic combines a greedy selection of rows and columns to be interchanged with an approach based on a genetic-inspired crossover. Several ideas of limiting the search tree are also investigated. Preliminary numerical experiments illustrate the fact that the proposed heuristic...

13 seconds. In future work, we intend to try multiple runs, or several populations with inter-population crossovers, and to randomize selection as well as crossover and mutation. It is certainly possible that our local improvement operator, applying the DAGparsimonious algorithm at every stage, is detrimental, or that better local improvement can be done. We intend to try an operator based on a...

In classification tasks, feature selection (FS) can reduce the data dimensionality and may also improve accuracy, both of which are commonly treated as two objectives in FS problems. Many meta-heuristic algorithms have been applied to solve problems they perform satisfactorily when problem is relatively simple. However, once datasets grows, their performance drops dramatically. This paper propo...

this paper considers the economic lot scheduling problem, that is, the problem of scheduling several products on a single facility so as to minimize holding and setup costs. combination of frequency and timing as well as production quantity make this problem np-hard. a heuristic is developed to obtain a good solution to elsp. the proposed heuristic makes use of the simulated annealing technique...

In this research, a new approach for tackling the permutation flow shop scheduling problem (PFSSP) is proposed. This algorithm based on steps of elitism continuous genetic improved by two strategies and used largest rank value (LRV) rule to transform values into discrete ones enabling solving combinatorial PFSSP. The first strategy combining arithmetic crossover with uniform give high capabilit...