This paper presents a computational comparison of nested Benders decomposit
ion and dynamic programming (DP) for stochastic optimisation problems arisi
ng from the optimisation of hydro-electric generation from hydraulically li
nked reservoirs. The examples considered have between 3 and 17 reservoirs,
two weather states, three runoff patterns and five periods. The examples ar
e solved exactly by the: simplex method and nested Benders decomposition an
d solved approximately by discrete dynamic programming (DP). A full version
of DP is used for examples with 3 and 4 reservoirs, and a decomposition me
thod is used for all examples. The full DP results are within 1% of optimal
and the DP decomposition results are within 3.2% of optimal. Timings are g
iven for serial and parallel versions of the algorithms. An analysis is giv
en of how the different methods scale with the number of periods, reservoir
s, weather states and runoff patterns, and also how applicable they are to
more general problems.