In this paper, to best describe the practical inventory situation,
we propose a general methodology based on a robust optimization
method to address the problem of multi-period dynamic pricing
and lot-sizing with generalized demand, deterioration, backorder
and purchasing cost functions. In addition, we also integrate a
two-level trade credit policy to fit more complex situations. As a
result, the presented study included numerous previous models as
special cases. The remainder of our paper is organized as follows:
In Section 2, we review the literature on time-varying demand and
cost, deterioration rate and trade credit financing. In Section 3, we
describe the assumptions and notation used throughout this study.
In Section 4, we establish the mathematical model. In Section 5,
a brief introduction to particle swarm optimization is presented.
Then, we prove that the optimal selling prices for in-stock and
stock-out periods over the planning horizon not only exist but are
unique for any given feasible replenishment scheme and provide
a lower bound of optimal selling prices to the problem. We also
provide a simple algorithm to find the optimal selling prices and