Transportation cost minimization of a manufacturing firm using genetic algorithm approach

This study utilizes a Genetic Algorithm in solving the transportation problem of a beverage producing company in Nigeria with a view to minimizing the total transportation cost and obtaining an optimal schedule or schedules using transportation cost data from the peak periods (January to April and August to December) in the 2014/2015 production year which witnessed a fifty per cent (50%) rise in the cost of diesel (a major contributor to the transportation cost) and a corresponding increase in its transportation cost as a result of government’s removal of subsidy on petroleum products. The obtained data were analyzed and formulated into a transportation matrix with three routes and ten depots which were coded into strings after which the GA was applied to generate optimal schedules for six to nine depots that optimize the total transportation cost, revealing marked savings when compared with the company’s current evaluation method. The cost savings reduced as the number of depots in the generated schedules increased with the six-depot schedule having the highest cost saving of N347, 552 daily. http://dx.doi.org/10.4314/njt.v35i4.2