Project Title: Further Development With Existing Search and Optimisation Algorithms 
Student: Elliot Charles
Course: MSc in Scientific Computation 

Abstract:
For a logistics company, planning out an efficient routing schedule is a computationally
complex task. Finding a solution that satisfies all customers demands’ and time windows
in a fixed time frame is difficult and can be fundamental for profitability in this industry.
Therefore, it is of upmost importance that quality solutions are able to be employed into
a logistical system.
To provide assistance on this problem, this study formulates and implements a multiobjective 
vehicle routing problem with time windows into two separate solvers, Gurobi and
OpenSolver. Five separate objectives were studied alongside testing, benchmarking solver
performance and a look into the pairwise relationship between objectives. The product
of this is a high performing optimiser, capable of reliably producing high quality routing
solutions to the MOVRPTW for different problem instances and results to reinforce the
pairwise relationship between objectives.