The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems. A new solution acceptance rule is proposed where, instead o...

The Asian green revolution trebled grain yields through agrochemical intensification of monocultures. Associated environmental costs have subsequently emerged. A rapidly changing world necessitates sustainability principles be developed to reinvent these technologies and test them at scale. The need is particularly urgent in Africa, where ecosystems are degrading and crop yields have stagnated....

We confront the job shop scheduling problemwith sequence dependent setup times and weighted tardiness minimization. To solve this problem, we propose a hybrid metaheuristic that combines the intensification capability of tabu search with the diversification capability of a genetic algorithm which plays the role of long term memory for tabu search in the combined approach. We define and analyze ...

Recent metaheuristics for mixed integer programming have included proposals for introducing inequalities and target objectives to guide the search process. These guidance approaches are useful in intensification and diversification strategies related to fixing subsets of variables at particular values. The authors’ preceding Part I study demonstrated how to improve such approaches by new inequa...

Recent adaptive memory and evolutionary metaheuristics for mixed integer programming have included proposals for introducing inequalities and target objectives to guide the search. These guidance approaches are useful in intensification and diversification strategies related to fixing subsets of variables at particular values, and in strategies that use linear programming to generate trial solu...

Ant colony optimization (ACO) algorithms are a recently developed, population-based approach which has been successfully applied to combinatorial optimization problems. However, in the ACO algorithms, it is difficult to adjust the balance between intensification and diversification and thus the performance is not always very well. In this paper we proposed an improved ACO algorithm in which a s...

BACKGROUND Sustainability in Agriculture In order to meet future needs of a growing human population and to achieve food security in the context of climate change, food production will likely need to increase—among other measures—while at the same time minimizing negative environmental impact (Foley et al., 2011). Sustainable intensification of agriculture (Garnett et al., 2013; Pretty and Bhar...

[1] Both El Niño-Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO) have previously been documented to impact Atlantic basin tropical cyclone (TC) activity through alterations in large-scale fields such as vertical wind shear, mid-level moisture, sea level pressure and sea surface temperature. Atlantic TC activity has been shown to be enhanced when La Niña conditions are presen...

We propose a synergistic approach to meta-heuristic search optimization algorithm. The fine balance between intensification (exploitation) and diversification (exploration) is very important to the overall efficiency and performance of a meta-heuristic search algorithm. Too little exploration and too much exploitation could cause the system to be trapped in local optima, which makes it very dif...