Shippers are emphasizing logistics, since networking has become complex due to the globalization and demand variability has become huge for various products across countries. In order to meet customer demands, vendors must ensure appropriate quantities of storages at the point of demand and must ensure optimal distribution plans that include routing of the distribution vehicles. Managing such complex logistic networks, with high level of customization and services expected by customers, require various strategies to keep the transportation and inventory costs low. This requirement has evolved as the Inventory Routing Problem (IRP) which focuses on timing of deliveries, sizes of shipments and routing of vehicles. With the objective of enabling logistics planners to determine the distribution quantities and routing schedules to warehouses, few prominent variants of the inventory routing problems are addressed. The proposed mathematical models and heuristic approaches can assist planners in logistic decisions at operational level. These approaches will be useful in Oil industries, Retail industries, Blood banks, Automobile Industries and Vendor managed inventory systems.

Vehicle Routing Problem (VRP) is an area which has been widely dealt with for the last four decades. Methodologies have been developed for many variants of the VRP. This work considers concurrent and sequential delivery and pick-up in VRPs, encountered in practice but rarely considered in theory. In addition, constraints on maximum route length and on time-windows have also been considered. Mathematical models incorporating such features have been developed. While the NP-hardness of these problems mandates the use of meta-heuristics, recognition of inherent characteristics of the problem led to the development of construction heuristics based on cluster analysis to obtain good feeder solutions that speed up the intensive search at the end. Genetic Algorithms (GA), an enhanced version of Simulated Annealing (ESA) and a hybrid of the two are the meta-heuristics proposed for optimization. The heuristics performed exceedingly well in the evaluations, recording better or equally good results in comparison to the existing methodologies.