The way in which strawberry plants propagate has been modelled mathematically and used to develop an algorithm that can help solve complicated problems. Writing in the International Journal of Innovative Computing and Applications, a team from Algeria has shown how such a plant propagation algorithm can be used to decide on an efficient nursing roster in a hospital.
Salim Haddadi of LabSTIC at the 8 Mai 1945 University in Guelma, explains that the nurse rostering problem is a combinatorial optimisation problem that has to be solved in every healthcare institution. It is a computationally hard problem with huge numbers of possible solutions and so requires a sophisticated approach that can find the optimal solutions from that huge number. There are many additional constraints on the solutions that might be tenable in a healthcare environment because nurses with different skills are needed at different times. There are also many regulations that must be complied with in the healthcare setting. Such constraints make solving the problem even tougher than a roster for shop assistants would be, for instance.
Plants have evolved many different propagation strategies. The most obvious is sexual reproduction which produces seeds that are dispersed by various mechanisms and grow into new plants. However, some plants, such as the strawberry plant can produce runners that branch from the main plant and generate new plants asexually with roots implanted from those new buds along the branches. The way in which strawberry plants project these runners and the positions of the new asexual offspring along the runners is determined by the plant’s sensing of sunlight, moisture levels, and nutrient concentrations. If conditions are inadequate when shorter runners are sent out, the parent plant will allow the runners to grow longer before a new plant bud forms to set roots. The algorithm models this process as a proxy for positioning nursing staff in the roster.
Haddadi, S. (2020) ‘Plant propagation algorithm for nurse rostering’, Int. J. Innovative Computing and Applications, Vol. 11, No. 4, pp.204–215.