This paper gives an overview of a study that was done on the logistics infrastructure used by the South African fruit industry. Given the increasing production and export volumes, development of new markets and the shortage of logistics infrastructure capacity during peak seasons, the SA fruit industry identified the need to investigate the optimal usage of existing infrastructure on a national level and to make recommendations with regards to the development of additional infrastructure. Some background on the SA fresh fruit industry and its export supply chain are provided. This is followed by a description of the four project phases and their deliverables. The paper is concluded with the key findings of the study.
(1), pp. 55-72. After a brief introduction to the problem, two models (a single-commodity graph theoretic model and a multi-commodity mathematical programming model) are derived for determining the maximal weekly flow or throughput of fresh fruit through the South African national export infrastructure. These models are solved for two extreme seasonal export scenarios and the solutions show that no export infrastructure expansion is required in the near future -observed bottlenecks are not fundamental to the infrastructure and its capacities, but are rather due to sub-optimal management and utilisation of the existing infrastructure.
This paper gives an overview of a discrete-event simulation study that was performed on pallet movement at Fresh Produce Terminals in the port of Durban, South Africa. The study formed part of an extended study of the logistics infrastructure of the South African fresh fruit industry and its export supply chain. The focus in this paper is on pallet movement in the terminal and its requirement on the storage capacity of the cold store facility. Specifics pertaining to input data analysis are provided, as well as a discussion of simulation model validation and output data analysis.
Recent technological advances have had a major impact on the management of traditional wineries, giving rise to the prospect of computerised decision support with respect to a range of complex harvesting and wine making decisions which have to be taken routinely. In this paper, two nested scheduling problems are considered. The first, referred to as the active cellar scheduling problem, is concerned with making good scheduling decisions within a winery (i.e. optimal assignments of grape intake batches to different processor sets inside the active part of the cellar). The harvest scheduling problem, on the other hand, refers to the larger, over-arching problem of selecting the best possible dates on which to harvest the respective vineyard blocks in order to preserve grape quality. A nested tabu search approach is presented to solve these two scheduling problems simultaneously. This solution approach has been implemented as a computerised decision support tool, called VinDSS, and the practical workability of this tool is demonstrated by means of a special case study at a winery in the South African Western Cape.
Apart from work in the mining industry during the 1950s, the first real Operations Research (OR) group in South Africa was established at CSIR in the early 1960s. Those initially involved in this group played a significant role in establishing OR at various universities in South Africa. The OR group at CSIR did, however, continue and today the group still exists. This paper presents a brief history of this group and endeavours to provide a glimpse of some of the projects conducted over the many years since its establishment.
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