Algorithm Design And Comparison for An Optimisation Problem & Road Network of Optilandia - LPG Gas Case Study - IT Assignment Help

Assignment Task -                 
 

Background 

In this assignment, you will address a real-world problem of delivery planning for the LPG (Liquefied  Petroleum Gas) distributor. In the areas where mains gas for heating purposes is not available, LPG is the closest alternative. It has the lowest carbon emissions per kWh out of all fossil fuels available in rural areas, does not pose any ground or water pollution hazards, and can be used for both heating and cooking. LPG distribution companies source the fuel from major oil refineries and deliver it to the bulk customers by a fleet tanker lorries like the one in Figure 1. 

You have been employed by SEO Gas Ltd as a data scientist. You are to produce delivery schedules for the fleet of 25 tanker lorries operating from 4 depots in the country of Optilandia (which surprisingly use £  as their currency), minimizing the overall cost of delivery for the distributor under certain constraints. 

Optimisation problems 

There are two problems you should address: 

1. Schedule LPG delivery to all customers in order to fully fill their tanks while minimising the overall cost of delivery. There are no additional constraints apart from the tanker lorry capacity – a lorry can for example visit any of the depots multiple times in order to load additional gas. 

2. Schedule LPG delivery in order to maximise the amount of gas delivered to the customers,  while minimising the overall cost of delivery (including any potential penalties! - see below)  and while observing the following constraints in addition to tanker lorry capacity: a. Each lorry can travel up to 250 miles 

b. Each lorry can only stop up to 5 times, this includes customer deliveries and any  additional visits to the depot 

c. Each lorry must end its journey in one of the depots (this doesn’t count towards the 5  stop limit and doesn’t have to be the depot from which the lorry started its journey) d. If you don’t deliver to customers who have less than 15% of gas in their tanks, SaO Gas  Ltd will incur a penalty of £1,000 for each such customer 

You are required to design and implement at least two optimisation schemes to address the LPG  delivery scheduling problems (that is two schemes in total, not two per each problem). One of these schemes can be simple e.g. a random or greedy scheduler, but you need to make sure that the approach  is able to generate valid solutions i.e. not violating the given constraints. You can use any combination of methods covered in class (e.g. Genetic Algorithms, Ant Colony Optimisation) as well as methods you  have found during your independent study or which you came up with yourself. 

Your implementation should be in Python. You are allowed to use existing Python optimisation libraries or implementations if you need to, but you should aim to implement as much as possible from scratch.

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