The management of waste with the limited workforce and trucks is a complicated problem.
Currently, there is insufficient evidence in literature on how this process could be optimised. In
this article, two new models on genetic algorithm and differential evolution were developed to
jointly optimise the cost and human reliability of a municipal solid waste (MSW). It optimised
this system’s benefit-cost and established the relationship between a MSW’s workforce and truck
allocation. Although prior research has revealed relationships among cost, workforce strength,
and truck allocation activities, however, the nature of this relationship and the unique attribute of
workers’ reliability to influence the total operating cost and the benefit-cost ratio have not been
thoroughly understood. A case study of a MSW agency in Nigeria was used to demonstrate the
applicability of the proposed model. The results obtained showed preference to the differential
evolution algorithm’s results. This article contributes to MSW in the following ways: it presents
a model to assign reliability to workforce in a MSW system based on evolutionary algorithms
performance, and it optimises a MSW system’s total operating cost and the benefit-cost ratio
concurrently.
Keywords
Reliability; Operating cost; Benefit/cost; Meta-heuristics; Municipal solid waste