A new concept for performing nuclear fuel optimization over a multi-cycle planning horizon is presented. The method provides for an implicit coupling between traditionally separate in-core and out-of-core fuel management decisions including determination of: fresh fuel batch size, enrichment and bundle design; exposed fuel reuse; and core loading pattern. The algorithm uses simulated annealing optimization, modified with a technique called mixing of states that allows for deployment in a scalable parallel environment. Analysis of algorithm performance for a transition cycle design (i.e. a PWR 6 month cycle length extension) demonstrates the feasibility of the approach as a production tool for fuel procurement and multi-cycle core design.
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