Transport and Routing model for collection of beer and distribution to a centralised Bottling Plant - Masjuan, Gonzalo (2013)
The UK brewing industry is valued at £28bn per year and provides over 700,000 jobs in the UK. A growing sector of this market (7% growth p.a.) is comprised of microbrewers who brew cask ale, a product worth £1.8bn and responsible for 45,000 jobs. There are now over 100 microbrewers in the East Midlands. In the UK, the domestic market for cask ale is extremely saturated and brewers are looking to expand their market by selling bottled beer in the same market and exporting abroad. However, bottling beer is currently extremely expensive and time consuming for microbrewers in the East Midlands region, since it is either bottled by hand or sent a considerable distance, as there is no contract bottling facility in the region. Recent research indicates that about 25% of the regional craft brewers in the East Midlands now bottle condition beer and others have expressed an interest in doing so. However, there are no contract bottling companies that are central to the East Midlands area and so beer is transported significant distances to be bottled and returned to the production brewery for distribution. This makes the process costly and environmentally less sustainable than it could be if a local facility were available. The scope of this dissertation is to identify the optimal solution for a fleet of vehicles, which will provide a collection and delivery service of beer, from a centralised Bottling Plant. The objective is to achieve reduction in CO2 emissions potentially generated by the introduction of a service of collection and delivery of beer from the Bottling Facilities. This dissertation explains why this problem is considered a Vehicle Routing Problem and how was resolved using the Cost Saving heuristic introduced by Clarke and Wright (1964), and later the Tabu Search metaheuristic introduced by Glover (1986). It is later explained how this heuristics were implemented using a macro in Microsoft Excel and the simulations obtained. The results show that the heuristic and metaheuristic combined generate a high quality solution, reducing considerable the CO2 emissions projected. However, some considerations before using the tool designed must be contemplated, therefore recommendations are given in this document. Finally, guidance, for the future end-user of the software implemented, is presented and future research directions are addressed.