Evolutionary algorithms applied to dynamic optimization problems has become a promising research area. So far, all papers in the area have assumed that the environment changes only between generations. In this paper, we take a first look at possibilities to handle a change during a generation. For that purpose, we derive an analytical model for a (1, 2) evolution strategy and show that sometime...

This paper reports on novel work using clonal selection (CS) for dynamic function optimisation. A comparison is made between evolution strategies (ES) and CS, for the optimisation of two significantly different dynamic functions at 2, 5 and 10 dimensions. Firstly a sensitivity analysis was performed for both the CS and the ES for both fitness functions. Secondly the performance of the two algor...

The ridge function class is a parameterised family of test functions that is often used to evaluate the capabilities and limitations of optimisation strategies. Past research with the goal of analytically determining the performance of evolution strategies on the ridge has focused either on the parabolic case or on simple one-parent strategies without step length adaptation. This paper extends ...

Efficient elevator group control is important for the operation of large buildings. Recent developments in this field include the use of fuzzy logic and neural networks. This paper summarizes the development of an evolution strategy (ES) that is capable of optimizing the neuro-controller of an elevator group controller. It extends the results that were based on a simplified elevator group contr...

this paper proposes an efficient algorithm based on memetic algorithm (ma) for a redundancy allocation problem without component mixing (rapcm) in a series-parallel system when the redundancy strategy can be chosen for individual subsystems. majority of the solution methods for the general rapcm assume that the type of a redundancy strategy for each subsystem is pre-determined and known a prior...

The cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. To enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. Normally, the parametersof the cuckoo search are kept constant. This may lead todecreasing the efficiency of the algorithm. To cop...

This paper defines head linear reduction, a reduction strategy of λ-terms that performs the minimal number of substitutions for reaching a head normal form. The definition relies on an extended notion of redex, and head linear reduction is therefore not a strategy in the exact usual sense. Krivine’s Abstract Machine is proved to be sound by relating it both to head linear reduction and to usual...

We de ne a perpetual one-step reduction strategy which enables one to construct minimal (w.r.t. L evy's ordering on reductions) in nite reductions in Conditional Orthogonal Expression Reduction Systems. We use this strategy to derive two characterizations of perpetual redexes, i.e., redexes whose contractions retain the existence of in nite reductions. These characterizations generalize existin...

This paper explores the use of the standard approach for proving runtime bounds in discrete domains—often referred to as drift analysis—in the context of optimization on a continuous domain. Using this framework we analyze the (1+1) Evolution Strategy with one-fifth success rule on the sphere function. To deal with potential functions that are not lower-bounded, we formulate novel drift theorem...