Update README.md

Author: dungtran209

README.md

@@ -5,14 +5,21 @@ A MSc's Dissertation Project which focuses on Vehicle Routing Problem with Time
 
 The exact approach is based on a classical Mix-Integer Programming (MIP) model and solved by IBM ILOG CPLEX 12.9. Both exact and heuristic algorithm are implemented by Python 3.7 and run on a ASUS Intel Core i7 with 1.8 GHz CPU and 8 GB RAM.
 
+
 ## Data
 Both methodologies are first tested on the famous Solomon (1987) benchmark instances. The data is avalaible on [SINTEF](https://www.sintef.no/projectweb/top/vrptw/solomon-benchmark/).
 
 Then, the methods are applied to solve an logistics problem in a UK-based company.
 
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 ## Methodology Summary
 
-**General Variable Neighbourhood Search (GVNS)**
+**1. Exact Method: Mathematical Formulations**
+
+MIP Model: [View](https://github.com/dungtran209/Modelling-and-Analysis-of-a-Vehicle-Routing-Problem-with-Time-Windows-in-Freight-Delivery/blob/master/algorithm/VRPTW%20MIP%20Model.pdf)
+
+
+**2. General Variable Neighbourhood Search (GVNS)**
 
 Pseudo-code: [View](https://github.com/dungtran209/Modelling-and-Analysis-of-a-Vehicle-Routing-Problem-with-Time-Windows-in-Freight-Delivery/blob/master/algorithm/GVNS%20pseudo-code.png)
 
@@ -28,5 +35,11 @@ Local Search Process | Variable Neighbourhood Descent (Best-accept strategy)
 Stopping Criteria | All neighbours (improvement operators) are explored
 
 
+## Visualization
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+Best solution (minimum total distance of all tours) found by the GVNS for benchmark instance R206 (100 customers)
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+![Image](https://github.com/dungtran209/Modelling-and-Analysis-of-a-Vehicle-Routing-Problem-with-Time-Windows-in-Freight-Delivery/blob/master/data/1.%20Sample%20Dataset/R206.100.png)
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