In this paper, xyzw model is introduced which characterizes the solid waste generated by the four departments in the university. Thus, the refuse on the street x, in the gutters y, in the dustbins z and dumpsite w. From the qualitative analysis of xyzw model, it revealed that the refuse in these departments piles up as the time increases indefinitely. Based on the analysis of data from the KNUST campus the refuse keeps on piling up. This reveals that the trucks are not able to adequately carry refuse from three departments: street, gutters and dustbins to the dumpsite as expected by the university authority. This comes as a result of overflows from the dustbins at some vantage points in the university. In practice, the waste in gutters and on street are collected and deposit it in these dustbins (with varying volumes) everyday, but the trucks are not able to convey all the quantum of waste in these dustbins to the dumpsite thereby resulting in refuse pile up on campus of the university
In this paper, a mathematical model is introduced to describe wastes pile-up in Kwadaso Municipality which categorize wastes on the streets X1(t), wastes in gutters X2(t), wastes in the dustbins X3(t), wastes in households X4(t), wastes in the market places X5(t) and the wastes sent to dumpsites X6(t). From the qualitative data, it was observed that wastes within the Municipal keeps on pilling up as time increases indefinitely. The increase is as a result of continuous enormous quantum generation of wastes which occur in the Municipality. It was also revealed that trucks were unable to carry out the expected task of carrying wastes to dumpsites regularly leading to daily overflow of wastes in Kwadaso Municipality.
The collection of solid waste from third class communities in most developing countries is by skip containers, however, the location of these facilities has been done arbitrary without any mathematical considerations as to the number of customers the facility is serving, the distance one has to travel to access it and thereby making some of these residences to dump their refuse in gutters, streams and even burn them. In this paper we proposed an improved probabilistic distance, capacity clustering location model which takes into consideration the weight of solid waste from a customer and the capacity of the skip container to locate the skip container to serve a required number of customers based on the capacity constraint of the container. The model was applied on a real world situation and compared with the existing practice in terms of average distance customers had to travel to access the facility. Our results gave a well shorter average travel distance by customers, gave a number of skip containers needed in an area based on their waste generation per capita.
Solid waste collection is an important issue in vehicle routing problem especially in the developing countries where most of the road network in the residential areas is very poor. A well planned path routing will go a long way to help waste management agencies to cut down cost of operations. This paper proposes a new vehicle routing path planning problem that assigns a tricycle to collect waste from individual household and dispose off into a skip bin within a defined cluster zone. The paper presents an Ant Colony optimisation algorithm that incorporates some new factors of selecting nodes such as weight, angle, saving and visibility to solve the vehicle routing path problem. The study is motivated by a real case in Ghana with the aim to optimize the collection of solid waste. The implementation of our improved algorithm gave about 18% reduction in distance travel compared with the traditional Ant Colony algorithm for vehicle routing path planning method.
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