Lot sizing with learning, forgetting and entropy cost

The lot sizing problem with learning and forgetting has received attention from many researchers. Most models in the literature adopt the classical approach of optimising the sum of two conflicting costs, which mainly are the holding and procurement costs. The results from these studies suggest that under learning effects, the optimal production policy is to deliver in smaller lots more frequently. Forgetting impedes performance and results in an optimal production policy that suggests having larger lots. Some recent studies have suggested that it might be possible to improve production systems performance by applying the first and second laws of thermodynamics to reduce system entropy (or disorder). Including entropy cost suggested that larger quantities should be ordered than is suggested by the classical EOQ model. This paper investigates the lot sizing problem taking account of learning, forgetting and entropy cost. Learning encourages producing in smaller lots while forgetting and entropy cost encourage the use of larger lots. Mathematical models are developed and numerical examples illustrating the solution procedure are provided.