Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Becoming culturally inclusive: A perspective on personnel preparation

It can be said that some of the topics and ideas that command our interest or attention are autobiographical in origin. This paper subscribes to this category. In this paper, I present a perspective on preparing professional personnel, namely, educators, practitioners, teachers, student teachers, and researchers, for cultural inclusion. This perspective is drawn from my experiences as a former postgraduate student from a culturally diverse background preparing for a career in severe disabilities and as a university educator who is interested in ways to encourage professionals in the field to be more cognizant of the influence of their cultural backgrounds and the value of becoming culturally inclusive.