Contents

• Tutorial 1 - Shortest Path
• Tutorial 2 - Nearest Customers
• Tutorial 3 - Elevator Simulation
• Tutorial 4 - Traveling Salesman Problem
• Tutorial 5 - Route Simulation
• Tutorial 6 - Vehicle Routing Problem
• Tutorial 7 - Parallel BLAS

1. Shortest Path

In Tutorial-1 you will learn how to use OR-Objects to build a graph like the one pictured and use it in a shortest path algorithm. This graph has seven vertices which are labeled 'A' through 'G'. It has ten edges which connect the vertices and there is a cost associated with each edge. Eight of the edges are undirected and the two with arrows are directed. An undirected edge is one that can be crossed in both directions and a directed edge is one that can only be crossed in a single direction.

2. Nearest Customers
	In Tutorial-2 you will build on what you learned in Tutorial-1 and use OR-Objects to construct a street network like the one to the left. Then you will customize a shortest path algorithm and use it to find customers nearest to the . The customers are labeled 'A' through 'J' and the  symbols are traffic lights. The 'L' and 'R' mark corners where left and right turns are not allowed.

3. Elevator Simulation
	In Tutorial-3 you will you will learn to use the exponential and empirical distributions in OR-Objects to simulate passengers entering an elevator system. An exponential distribution is used to generate the passenger arrivals and two empirical distributions are used to determine the origination and destination floors.

4. Traveling Salesman Problem
	In Tutorial-4  you will learn to use OR-Objects to model the problem pictured to the left. A supply service is located at the depot and uses a helicopter to make deliveries. The problem is to design a tour which connects all the selected customers to the depot while minimizing the flight distance.

5. Route Simulation

In Tutorial-5 you will use the street network that was introduced in Tutorial-2 to simulate a service route. A single vehicle is located at the depot and each day it must visit all the customers that demand service. The customers that require service vary randomly and are known at the start of the day. The simulation will determine the expected time the vehicle will spend traveling to customers each day based on the average daily demand.

6. Vehicle Routing Problem

In Tutorial-6  you will extend the problem introduced in Tutorial-4. The supply service located at the depot now has a fleet of helicopters. The problem is to design delivery routes to serve all customers while minimizing the flight distance and not exceeding the load capacity or range of the helicopters. A red dot () marks a customer demanding a 300 kilogram payload. A yellow () payload weighs 200 kilograms and a green () weighs 100 kilograms.  The black dot () marks the depot. This tutorial also introduces geometric transform objects which are used to convert between the geographic, map and screen coordinate systems.

7. Parallel BLAS
	In Tutorial-7  you will develop an applet to measure the scalability of the matrix multiply in the parallel BLAS implementation. The applet computes the rate of floating point operations for thread counts of '1' to '16'. The rate will scale on Java virtual machines that use native threads and are running on an SMP platform that distributes threads across multiple processors.