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In this paper we present a new algorithm of steepest descent type. A new technique for steplength computation and a monotone strategy are provided in the framework of the Barzilai and Borwein method. In contrast with Barzilai and Borwein approach's in which the steplength is computed by means of a simple approximation of the Hessian in the form of scalar multiple of identity and an interpretation of the secant equation, the new proposed algorithm considers another approximation of the Hessian based on the weak secant equation. By incorporating a simple monotone strategy, the resulting algorithm belongs to the class of monotone gradient methods with linearly convergence. Numerical results suggest that for non-quadratic minimization problem, the new method clearly outperforms the Barzilai-Borwein method.

Fish tilapia Oreochromis mossambicus were collected from a contaminated Seri Serdang (SS) pond potentially receiving domestic effluents and an uncontaminated pond from Universiti Putra Malaysia (UPM). The fish were dissected into four parts namely gills, muscles, intestines, and liver. All the fish parts were pooled and analyzed for the concentrations of Cd, Cu, Fe, Ni, Pb, and Zn. Generally, the concentrations of all metals were low in the edible muscle in comparison to the other parts of the fish. It was found that the levels of all the heavy metals in the different parts of fish collected from the SS were significantly (P<0.05) higher than those from UPM, indicating greater metal bioavailabilities in the SS pond. The sediment data also showed a similar pattern with significantly (P<0.05) higher metal concentrations in SS than in UPM, indicating higher metal contamination in SS. Potential health risk assessments based on provisional tolerable weekly intake (PTWI) and the amount of fish required to reach the PTWI values, estimated daily intake (EDI), and target hazard quotient (THQ) indicated that health risks associated with heavy metal exposure via consumption of the fish's muscles were insignificant to human. Therefore, the consumption of the edible muscles of tilapia from both ponds should pose no toxicological risk of heavy metals since their levels are also below the recommended safety guidelines. While it is advisable to discard the livers, gills, and intestines of the two tilapia fish populations before consumption, there were no potential human health risks of heavy metals to the consumers on the fish muscle part.

The performance of a genetic algorithm is dependent on the genetic operators, in general, and on the type of crossover operator, in particular. The population diversity is usually used as the performance measure for the premature convergence. In this paper, a fuzzy genetic algorithm is proposed for solving binary encoded combinatorial optimization problems. A new crossover operator and probability selection technique is proposed based on the population diversity using a fuzzy logic controller. The measurement of the population diversity is based on the genotype and phenotype properties. In this fuzzy inference system, the selection of the crossover operator and its probability are controlled by a set of fuzzy rules derived from the fuzzy logic controller. Extensive computational experiments are conducted on the proposed algorithm, and the results are compared with some crossover operators commonly used for solving multidimensional 0/1 knapsack problems published in the literature. The results indicate that the proposed algorithm is effective in finding better quality solutions.