Following is a description of 17 miniprojects. Each miniproject involves preparing a comprehensive technical paper and carrying out a substantial programming project both of which are closely related. About three students can collaborate on each miniproject. Each group should send me an email, before September 25, indicating the members of the team and a list of 4 projects, one of which will be assigned to the team.

Guidelines for preparing the term paper and a Latex style file for the same are provided in a separate note. Here is the schedule:

September 27, 2000 Allocation of projects to groups
October 10, 2000  Each group will provide a detailed outline of the term paper and also a detailed specification for the programming assignment
October 20, 2000  Review of final specifications for the programming project
October 31, 2000  Deadline for submitting the term paper
November 10, 2000  Deadline for Programming Project submission
Nov 13-17, 2000  Demos of programming projects
The projects fall into four categories:
Strategic Planning (SP)
Operational Optimization (OO)
Performance Modeling (PM)
Web-enabled Supply Chains (WEB)
(1) It is expected that projects belonging to a category are interoperable. The ultimate objective is to make  projects interoperable across categories.
(2)  Many of the miniprojects will involve computational solvers (LP, ILP, MILP, linear equations, etc.).  Public domain software for these will be made accessible from this webpage soon for this purpose.
(3)  What is currently outlined here is a first level description of the problems. You can peruse the leads provided here and do your own search for relevant material (Journal Papers, web resources, etc) towards evolving a detailed outline for your term paper on this topic  and  towards defining the specifications for the programming project.
(4) If you are unable to download or access the lead papers, contact  hari@csa, or biswas@csa, kameshn@csa, or raju@csa for the material.


Students interested in these projects should have a sound understanding of optimization fundamentals. The implementation will need good computational skills since the problems can turn out to be large scale.
SP1: Location of Supply Chain Facilities

Gopal Malakar, Bishal, Prakash Bhandari

The geographic location of production facilities, stocking points, and sourcing points is an important strategic planning step in supply chain design. Once the size, number, and location of supply chain facilities are determined, so are the possible paths by which the product flows through to the final customer. These decisions have great significance since they determine the way in which customer markets are accessed and they have substantial impact on revenue, cost, and service levels. The location problem has been formulated by several researchers as a mixed linear integer programming problem (MILP).

Lead: B.C. Arntzen, G.G. Brown, T.P. Harrison, and L. Trafton. Global supply chain management at the Digital Equipment Corporation, INTERFACES, Jan-Feb 1995.
SP2: Supply Chain Configuration
The decisions here include what products to produce, which plants to produce them in, allocation of suppliers to plants, plants to distribution centres, and distribution centres to customer markets. These decisions assume the existence of supply chain facilities but determine the exact paths through which a product flows to and from these facilities.

Leads: (1) www.i2.com has details of i2's "Supply Chain Strategist" package.
(2) R.L. Breitman and J.M. Lucas. PLANETS: A modeling system for business planning, INTERFACES, Jan-Feb 1987, pp. 94-106.
SP3: Procurement Planning

Neeraj, Tejas, Shashikala, Maya

Procurement planning takes an unbiased forecast of expected sales and performs a number of computations to obtain a corresponding set of part requirements. It is a critical process in the determination of a company's serviceability and inventory. This function becomes an interesting optimization problem if there is constrained supply and uncertain demand.

Lead: B. Dietrich et al. Production and Procurement planning under resource constraints and demand variability. Research Report, IBM Research  Laboratory, Yorktown Heights, 1995.
SP4: Distribution Facilities Planning

Madhav Goswami, Amit Nimje, Pankaj Kumar

This involves determining the number, location, capacity, and layout of an optimal distribution network to maximize customer service levels given the demand distribution and other supply chain parameters.

Lead:  A. Geoffrion and R. Powers. 20 years of strategic distribution system design: An evolutionary perpspective, INTERFACES, Sept 1995.
SP5: Logistics Planning
This involves selecting the best mode of logistics by trading off cost of using a particular mode with inventory costs. Geographic locations play an important role in the problem. Other decisions include designing a logistics network for optimizing product flows from plants to distribution centres to final customers.

Lead: CAPS LOGISTICS specializes in this kind of solutions.


Students interested in these projects should have a sound understanding of optimization fundamentals. The implementation will need good computational skills since the problems can turn out to be large scale. Some familiarity with stochastics will be a bonus.
OO1: Supply Chain Inventory Optimization

Krishnakumar, Shankar Ganigi

Inventories exist in every stage of supply chains, as raw materials, work in process, finished goods inventory, etc. The primary purpose of inventory is to buffer against uncertainties and to maintain acceptable customer service levels. Since inventory is expensive, maintaining optimal inventory levels in supply chain stocking points is an important problem. Economic order quantity models, statistical inventory control policies, and Multiechelon inventory management have been used in this context.

Leads: (1) M. Ettl, G.E. Feigin, G.Y. Lin, and D.D. Yao. A supply chain network model with base stock control and service requirements. IBM Research Report, 1996. Available from: www.ibm.watson.com
(2) M.A. Cohen et al. OPTIMIZER: IBM's muti-echelon inventory system for managing service logistics, INTERFACES, Volume 20, Jan-Feb 1990, pp. 65-82.
OO2: Advanced Scheduling

AP Mohanty, Rajasekhar, Tripathi

i2's RHYTHM suite of products includes an Advanced Scheduler which performs the detailed synchronization of all production operations to meet customer goals and optimize resources. It determines the optimal sequence of jobs, taking into account a variety of realistic and detailed constraints. It uses tools such as genetic algorithms and constraint optimization for this purpose. The objective of this project is to develop a scaled down , but high-utility version of this Advanced Scheduler.
OO3: Logistics Resources Scheduling
Vehicle routing and scheduling, and fleet management are important tactical and operational decisions in supply chain networks. CAPS LOGISTICS is a best practice company specializing in this important problem. The goal of this project will be to survey the best practices in the area and create a tool that can be deployed in decision support for fleet management and routing and scheduling of vehicles.


PM1: An Object Oriented Modeling System
Sanjay Linda, Ramesh Kumar, Bharat Biswal

The goal of this project is to design and develop a library of supply chain objects (structural, policy, and informatio-related) and provide a versatile tool for rapidly creating object oriented models of specified supply chain networks. It should be possible to use the models so created in the other tools that will be created  through miniprojects.  For example, it should be possible to use the OO-model to formulate the inventory optimization  problem, to  set up a simulation model of a supply chain, to provide the information for an order tracking system, etc.

Prerequisites: Sound familiarity with objects, UML, Java

Leads: (1) S. Biswas and Y. Narahari. Object oriented modeling for decision support in supply chain networks, Research Report, 1999.

(2) IBM Supply Chain Simulator
PM2: Dynamic Simulation of Supply Chains

KV Sriram and Atul Malik

The objective here is to create an object oriented discrete event simulation environment for supply chain networks. The vision is to  design and develop an environment as powerful and versatile as that of IBM supply Chain simulator.

Prerequisites: Queueing, Markov chains, simulation, data structures, Java

Leads: Literature on IBM supply chain simulator
PM3: A Queueing Network Based Supply Chain Planner

DN Pawar, MS Hari, Behera

Queueing networks are appropriate for many situations in supply chain planning, analysis, and design. The idea is to create a queueing network model from the object oriented description of a supply chain and use queueing results to provide what-if type of decision support in supply chain planning and design. The vision is to develop a package for supply chains on the same lines as MANUPLAN and MPX (University of Wisconsin, Madison).

Prerequisites: Queueing, Markov chains, simulation, data structures, Java
PM4: A Six Sigma Framework for Analysis and Design of Supply Chain Networks

Dinesh Garg, Sandeep, Anand Prasanna

Assuming normal distributions for business process lead times and using the notions of Cp and Cpk, this tool will be fashioned as (1) an analysis tool to determine the delivery performance of any complex supply chain
and as  (2) a synthesis tool for designing supply chains to achieve specified levels of delivery performance.

Prerequisites: Probability and statistics, Java

Leads: There are two excellent reports on the Motorola six sigma program.


For all the projects in this category, familiarity with Internet technologies, Java technologies, and database technology will be required.

General Reading:
Establishing an E-commerce Business Model
Going, Going, Gone! A Survey of Auction Types
EcomWorld: Automating the Supply Chain
WEB1: A Web-enabled Procurement System

Sivaramakrishna, Praveen Kumar, Kaushik

Procurement involves multiple suppliers and a single buyer and the goal of this system is to design and develop a web-enabled procurement system using interesting web-based mechanisms. Sealed bids (single round and multiple round), etc. can be implemented here.

Leads: Numerous web sites, e.g:
EcomWorld: Procurement
Priceline.com: An Inside Look at the Reverse Auction Master
WEB2: A Web-enabled B2B Exchange for Supply Chain Management

Vasudeva Rao, Murlimohan, Hariharan

An exchange involves multiple sellers and multiple buyers and effects efficient matching using web-based mechanisms.  Exchanges can be either horizontal or vertical. B2B exchanges are now an integral part of major supply chains. The project can focus on  creating the web infrastructure for a scaled down vertical exchange.


Digital Exchanges: Value or hype?
WEB3: A Web-enabled order tracking system

Balvinder Singh, Himanshu

The objective is to design a monitoring and tracking system that continuously tracks the flow of material, information, and customer orders through supply chain stages and provides real-time, up-to-date information to external and internal customers. The order tracking system will monitor the supply chain through a database that is dynamically and continuously updated by  simulating an underlying model of a supply chain network. The vision  is to create a replica of amazon.com's tracking system.

Leads: Numerous web sites
Elbee: Logistics Provider of FirstandSecond.com
FedEx Tracking System, India
UPS ECommerce
WEB4: Warehouse Management System

Abhijit, Satyendra, Srivalli

Consider an arborescent, multiechelon warehouse network (Plant warehouse, Ditribution centres, retailers, etc.).  Warehouse management involves keeping track of levels of inventory of multiple product types at each warehouse, placing replenishment orders,  handling backorders, managing and tracking  customer orders on the web.  This project will involve not only web enabling of the system but also incorporating  specified inventory control policies at individual warehouses. The system should be able to trigger  a procurement activity or  participating in a B2B exchange for doing replenishment if the source warehouses do not have adequate stock.

Requirements: Good understanding of EOQ models, (Q, r) policies, etc.

Softsol: eWarehouse Management   (Cached)
Logistics.About.com: Warehouse Management
WEB5: Customer Relationship Management

Subhash Das, Sridhar Reddy, Srimanta Mohanty

Which visits lead to Purchases? Dynamic Conversion behaviour at EComm Sites  (Thanks to Sriram ofIbhar. A good lead for CRM in EComm)

Course Orgainzation & Overview 
Course Schedule 
Books and References
Term Papers 
Mini Projects 
Useful Web Resources

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