MatHeuristic Approach for Production-Inventory-Distribution Routing Problem

Abstract

In this paper, the integrated Production, Inventory and Distribution Routing Problem (PIDRP) is modelled as a one-to-many distribution system, in which a single warehouse or production facility is responsible for restocking geographically dispersed customers whose demands are deterministic and time-varying. The demand can be satisfied either from inventory held at the customer sites or from daily production. A fleet of homogeneous capacitated vehicles for making the deliveries is also considered. Capacity constraints for the inventory are given for each customer and the demand must be fulfilled on time. We propose a two-phase approach within a MatHeuristic framework. Phase I solves a mixed integer programming model which includes all the constraints in the original model except the routing constraints. In phase 2, we propose a variable neighborhood search procedure as the metaheuristics for solving the problem. We carried out a statistical analysis and the findings showed that our results are significantly superior to those from the Greedy Randomized Adaptative Search Procedure (GRASP) in all instances. We also managed to improve 23 out of 30 instances when compared to the Memetic Algorithm with Population Management (MA|PM). The superiority of our algorithm is reemphasized when tested on larger instances with the results showing significantly improved solutions by 100% and 90% respectively when compared to GRASP and MA|PM.