Algorithms for vendor managed inventory routing and machine scheduling models

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1. Introduction/Overview***This proposal aims to contribute towards the advancement of knowledge in the area of logistics, transportation and operations research with a purpose to disseminate this knowledge to both academics and practitioners. This research proposal will particularly focus on two important topics of supply chain management 1) vendor managed inventory problem and 2) two agents based scheduling problem. Vendor Managed Inventory (VMI) is one of the ways a supply chain can improve its performance by reducing cost and improving service. This is one of the successful business models used by Wal-Mart, Shell Chemicals and other retailers. The scheduling of jobs with two agents arises in many business areas such as telecommunications, integrated multimedia services, rail road tracks, manufacturing industry, maintenance planning etc. ***2. Proposed Models:***I. VMI Infinite time horizon model: This model would assume that mean demand for each customer is known and constant. Most of the papers in literature consider the base cycle time to be a decision variable. However, practitioners prefer a convenient base cycle time such as one week, two weeks or a month for transportation planning purposes. Our model would assume a fixed base cycle time which will be specified by the manager. ***II. VMI Finite time horizon model: This type of model minimizes the total inventory and transportation cost assuming a time dependent product demand. We will focus upon the single depot, multiple customers, time dependent demand and order-up-to-level replenishment policy model. ***III. Two agents based scheduling problem with switch over time: The existing literature on two agents based scheduling model does not consider switch over time between different agents. A switchover time arises whenever a job of one agent is processed after a job of another agent. The concept of switchover time is similar to the setup time used in the literature of scheduling. ***3. Proposed Methods:***We will develop heuristics and meta-heuristics based solution techniques for the integrated models. These solution techniques will be coded in C or C++ programming language and an experiment will be performed with benchmark problem instances. ***4. Anticipated outcome of the program:***The proposed problem falls under category of NP-hard problems for which getting optimal solution is practically very difficult. The program will design solution methods for finding near optimal solution for the different models. ***5. Training to take place through the proposal***One PhD student and three Master students will be recruited for this program. PhD and Master's students will be trained in developing mathematical and computer models for the problem.***6. Anticipated significance of the work:***The proposed research has the potential to improve supply chain operations by providing managers with a framework to minimize the production, transportation and inventory cost.