A Workforce and Truck Allocation Model in a Solid Waste Management System: A Case from Nigeria

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.

Truck dispatching and minimum emissions earthmoving

Purpose – The dispatching of trucks in earthmoving and like operations is worthy of examination because of potential emission reductions and savings through the appropriate allocation of trucks to excavators and dump sites. The paper aims to discuss this issue. Design/methodology/approach – Truck dispatching is performed through linear programming (LP) and the effect of truck allocation on unit emissions and unit costs established. Number of trucks, unit cost and unit emissions are all considered as objective functions. A cut and fill operation on a road project provides a numerical case study. Findings – It is demonstrated analytically that the minimum unit emissions solution is the same as that for minimum unit cost. Numerical results from the case study, including sensitivity analyses on the underlying parameters, support this conclusion. Practical implications – The LP dispatching solution, based on minimizing truck numbers and unit costs, accordingly impacts the environment the least in terms of emissions. The paper's results will be of interest to those designing and managing earthmoving and like operations for production, cost and emissions. Originality/value – While LP has been used by others to examine optimum unit cost dispatching, this paper is original in examining the dispatching or truck allocation based on both unit cost and unit emissions, and showing the relationship between the optima for both.