In deterministic systems, reinforcement learningbased online approximate optimal control methods typically require a restrictive persistence of excitation (PE) condition for convergence. This paper presents a concurrent learningbased solution to the online approximate optimal regulation problem that eliminates the need for PE. The development is based on the observation that given a model of th...

The linear systems with separable matrices arising from the nite diierence discretization of constant-coeecient elliptic equations in rectangles are considered. A new direct method is proposed and analyzed for the approximate solution of general partial solution problems for such systems of grid equations. This method can be used also with quasiuniform discretization grids, whereas the earlier ...

In supply chains, domestic and global, a producer must decide on an optimal quantity of items to order from suppliers and at what inventory level to place this order (the EOQ problem). We discuss how to modify the EOQ in the face of failures and recoveries by the supplier. This is the EOQ with disruption problem (EOQD). The supplier makes transitions between being capable and not being capable ...

Traditional solution methods such as search and sort for optimising complex real life engineering problems can be very expensive in terms of computational time. The considerable execution time tends to inhibit elaborate exploration of the design space and often results to sub-optimal solutions. This paper reports on an engineering optimisation approach designed to bridge the gap between traditi...