Department of Logistics

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Browsing Department of Logistics by browse.metadata.advisor "Bezuidenhout, C. N."

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    Tactical sugarcane harvest scheduling
    (Stellenbosch : University of Stellenbosch, 2010-12) Stray, Bjorn Jonas; Van Vuuren, J. H.; Bezuidenhout, C. N.; University of Stellenbosch. Faculty of Economic and Management Sciences. Dept. of Logistics
    ENGLISH ABSTRACT: Computerised sugarcane harvest scheduling decision support is an active fi eld of research which ties in closely with the broader problem of automating and streamlining the various activities in the sugar supply chain. In this dissertation, the problem of providing decision support with respect to sugarcane harvesting decisions is defined within a number of contexts, each representing a typical kind of organisation of sugarcane farmers into a cohesive decision making unit with its speci fic requirements and limitations that exist in practice. A number of variations relevant to these contexts of an overarching tactical sugarcane harvest scheduling problem (THSP) are considered and solved in this dissertation. The THSP is the problem of providing objective, responsible decision support to persons charged with the task of determining optimal harvesting dates for a set of sugarcane fields across an entire season. Sugarcane fields typically diff er in terms of the age, variety, life-cycle stage and in many other properties of the cane grown on them. The growth of sugarcane crops may also be a ffected by environmental conditions such as accidental fires, frosts or storms which have a detrimental e ffect on crop-value. Since sugarcane is a living organism, its properties change over time, an so does the potential pro t associated with it. The practicalities of farming cause further complication of the problem (for example, seasonal changes alter the conditions under which the crop is harvested and transported). The rainy season carries with it the added cost of disallowing long-range vehicles to drive into the fields, forcing the unloading and reloading of cane at so-called loading zones. Other considerations, such as the early ploughing out of fields to allow them to fallow before being replanted, compounds the THSP into a multi-faceted difficult problem requiring efficient data management, mathematical modelling expertise and efficient computational work. In the literature the THSP has been viewed from many different standpoints and within many contexts, and a variety of operations research methodologies have been employed in solving the problem in part. There is, however, no description in the literature of a solution to the THSP that takes the negative e ffects of extreme environmental conditions on the quality of a harvesting schedule into account in a scienti fically justifi able manner; most models in the literature are based on optimising sucrose yield alone under normal conditions, rendering weak schedules in practice. The scope of the modelling and solution methodologies employed in this dissertation towards solving the THSP is restricted to integer programming formulations and approximate solution methods. The parameters associated with these models were determined empirically using historical data, as well as previous work on deterioration of sugarcane following environmental and other events. The THSP is solved in this dissertation by designing a generic architecture for a conceptual decision support system (DSS) for the THSP in the various contexts referred to above, which is capable of accommodating the e ects of extra-ordinary environmental conditions, as well as the introduction of a computer-implemented version of a real DSS for the THSP conforming to the framework of this generic architecture. The DSS building blocks include prediction models for sugarcane yield, sugarcane recoverable value under normal circumstances, the costs associated with a harvesting schedule and the negative e ects on sugarcane recoverable value of extraordinary environmental conditions. The working of the DSS is based on a combinatorial optimisation model resembling the well-known asymmetric traveling salesman problem with time-dependent costs which is solved approximately by means of an attribute-based tabu search in which both local and global moves have been incorporated. The DSS is also validated by experienced sugarcane industry experts in terms of the practicality and quality of the schedules that it produces.