Abstract. Artificial Bee Colony (ABC) algorithm is a well known swarm intelligence algorithms which have been shown to perform competitively with respect to other population-based algorithms. However, this algorithm has poor exploitation ability. To address this issue, constrained Artificial Bee Colony (cABC) algorithm is proposed where three new solution search equations are introduced respectively to employed bee, onlooker bee and scout bee phases. This algorithm is tested on several constrained benchmark problems. The numerical results demonstrate that the cABC is competitive with other state-of-the-art constrained ABC algorithms under consideration.

We aimed to reparameterize and validate an existing dengue model, comprising an entomological component (CIMSiM) and a disease component (DENSiM) for application in Malaysia. With the model we aimed to measure the effect of importation rate on dengue incidence, and to determine the potential impact of moderate climate change (a 1 °C temperature increase) on dengue activity. Dengue models (comprising CIMSiM and DENSiM) were reparameterized for a simulated Malaysian village of 10 000 people, and validated against monthly dengue case data from the district of Petaling Jaya in the state of Selangor. Simulations were also performed for 2008-2012 for variable virus importation rates (ranging from 1 to 25 per week) and dengue incidence determined. Dengue incidence in the period 2010-2012 was modelled, twice, with observed daily weather and with a 1 °C increase, the latter to simulate moderate climate change. Strong concordance between simulated and observed monthly dengue cases was observed (up to r = 0·72). There was a linear relationship between importation and incidence. However, a doubling of dengue importation did not equate to a doubling of dengue activity. The largest individual dengue outbreak was observed with the lowest dengue importation rate. Moderate climate change resulted in an overall decrease in dengue activity over a 3-year period, linked to high human seroprevalence early on in the simulation. Our results suggest that moderate reductions in importation with control programmes may not reduce the frequency of large outbreaks. Moderate increases in temperature do not necessarily lead to greater dengue incidence.

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In this paper, we propose a new hybrid conjugate gradient method for unconstrained optimization problems. The proposed method comprises of beta (DY), beta (WHY), beta (RAMI)  and beta (New). The beta (New)  was constructed purposely for this proposed hybrid method.The method possesses sufficient descent property irrespective of the line search. Under Strong Wolfe-Powell line search, we proved that the method is globally convergent. Numerical experimentation shows the effectiveness and robustness of the proposed method when compare with some hybrid as well as some modified conjugate gradient methods.

In this paper, the convergence analysis of a proposed new conjugate gradient method for unconstrained optimization problems was considered. This method inherits an important property of Polak-Ribiere-Polyak (PRP). Under the exact line search condition, we established the descent condition of the method as well as the global convergence of the method. Numerical results show that our formula is effective by comparing with some existing formulas.

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An iterative algorithm, which is called the integrated optimal control and parameter estimation algorithm, is developed for solving a discrete time nonlinear stochastic control problem. It is based on the integration of the principle of model-reality differences and Kalman filtering theory, where the dynamic integrated system optimization and parameter estimation algorithm are used interactively. In this approach, the weighted least-square output residual is included in the cost function by appropriately monitoring the weighted matrix. An improved linear quadratic Gaussian optimal control model, rather than the original optimal control problem, is solved. Subsequently, the model optimum is updated using the adjusted parameters induced by the differences between the real plant and the model used. These updated solutions converge to the true optimum, despite model-reality differences. For illustration, the optimal control of a nonlinear continuous stirred tank reactor problem is considered and solved by using the method proposed.

Trapping of neutrophils within the lung occurs in patients undergoing haemodialysis and is also a possible mechanism in the pathogenesis of bronchial hyper-responsiveness. Falls in peak expiratory flow rate occur in most dialysis patients, and some develop overt asthmatic symptoms. To see whether these changes in airway function are secondary to increases in bronchial reactivity during haemodialysis, we therefore performed histamine challenge testing in 6 non-asthmatic patients before and after haemodialysis. No change in reactivity was observed, suggesting that haemodialysis does not commonly result in bronchial hyper-reactivity in non-asthmatic individuals.