Integrated production-inventory and pricing decisions for a single-manufacturer multi-retailer system of deteriorating items under JIT delivery policy

Abstract

This paper studies an integrated optimization problem of production-inventory and retail pricing decision for a single-manufacturer multi-retailer system of deteriorating items under just-in-time (JIT) delivery environment. The objective of the model is to maximize the total profit of the system which equals to the total revenue minus the total cost. The features of the model lie in three facets: first, revenue is dependent on the demand and selling price, while demand is price sensitive; second, transportation costs between manufacturer and retailers are included in assessing the total cost, and third, customer service level constraint is also considered in the model. Since the model is a complex mixed-integer nonlinear programming (MINLP) model, it is difficult to derive a closed-form solution using classic differentiation methods. In this paper, two meta-heuristic algorithms, particle swarm optimization (PSO) and quantum-behaved PSO (QBPSO) are developed to solve the model. Experiments show that QBPSO is more effective and more efficient than basic PSO. Sensitivity analysis reveals the impact of model parameters on solution, and some important managerial implications on the JIT strategy are summarized.