Obligaciones Internacionales de los Estados
1. atribuciones y facultades
1.1 Background
The problem of constructing a suitable schedule for the harvesting of sugarcane dates back to the period 6 000 BC to 500 BC, when the cultivation of this species of the grass family, Poaceae (earlier Gramineae), began in New Guinea and continued at a larger scale in India [62], having followed the human migration routes between Melanesia and South-east Asia [172]. The Persian Emperor Darius discovered “the reed which gives honey without bees” during his 510 BC intrusion into India Proper and brought it home to Persia, where honey was the only known sweetener at the time [189]. Alexander the Great discovered “the sacred cane” [210] during his two-year India campaign from 327 to 326 BC [210, 232], for the benefit of the Mediterranean nations [201].
It was, however, not until the Arab invasions of Persia in 633, 636 and 642 AD [229] that Saccharum officinarum, or “noble cane” (the sweetest species of the Saccharum genus), S. spontaneum (the species occurring in the wild), S. barberi (the most important species used in breeding) and S. robustum (the hard stalked species) [54] began to spread seriously, reaching Egypt in 710 AD [89], Spain in 755 AD, Sicily in 950 AD [15, 34] and was eventually brought by Columbus to Hispaniola on November 22, 1493 during his second journey to the Americas [230, 231]. In 1518, the Portuguese established the first sugarcane plantation in Brazil [218], today the largest sugar producer in the world, having a few decades earlier colonised some of the islands off the west coast of the African continent, namely Madeira and Sao Tome, successfully cultivating sugarcane on a large scale [62].
The southward spread of sugarcane cultivation and refining from Egypt—refining and re-crystalli- sation having been invented by the Egyptians [89]—to southern and eastern Africa occurred rather gradually during the period 1500–1850 AD. However, the Dutch introduced sugarcane to Mauritius prior to surrendering the island to the French in 1710 [151].
The first colonial sugar plantations in South Africa were established in Natal (currently KwaZulu- Natal) during the period 1846–1855 [10,197], the first plantation being Compensation in Umhlali established by a Mr Edmond Morewood who acquired his seed cane from Mauritius and Re- union [197]. Land had been opened to white settlers due to the annexation of Natal by order of the Cape Governor, Sir George Napier, on 31 May 1844 [185]. However, some claim that sugarcane was already grown by the Zulus at least as early as the 17th century [10].
From the 1850s onward, sugarcane growers established themselves throughout Natal, some im- migrating from Europe or Mauritius, lured by word of profitability stemming from initial suc- cess [197], while many workers were “recruited” as indentured labourers from India during the 1860s [196]. The general trend during the 20th century was for sugarcane farms to expand, the
initially small, scattered mills to be consolidated and for large sugar companies to emerge. Some farms remain small to this day, other farms have merged into large, family-owned farms while still others have become incorporated into commercial estates. This relative diversity today makes up the fourteen established mill supply areas from Mpumalanga Province in the north to southern KwaZulu-Natal, contained within the areas indicated in Figure 1.1. The approximately 47 000 sugarcane farms in South Africa [194] currently produce more than 20 million tonnes of sugarcane per annum, resulting in approximately 2.3 million tonnes of sugar each year [108].
Figure 1.1: Shaded areas indicate the cultivation of sugarcane in South Africa.
1.2 Informal problem description
Increasing global competition in the international marketplace, mainly spearheaded by the Brazilian and Indian sugar industries, results in sugar prices remaining relatively low world- wide [55]. However, increasing fuel prices, perhaps currently driven by the rate of depletion of
1.2. Informal problem description 3 fossil fuels and the emerging industrial giants, China and India [228], are raising operational costs of farming. A mill supply area may comprise several thousand subsistence farmers, sev- eral hundred commercial growers and a few very large estates [194]. The commercial growers and large estates are, from a purely economical perspective, more important. For example, 83 % of the sugarcane milled in South Africa by Tongaat Hulett Sugar, one of the large sugar companies, is grown on company land or large commercial farms, while only 17 % is grown on small and medium-scale farms [215]. Increasing pressure from the global market on the South African sugar supply chain [135] combined with the fact that sugarcane is an age-deteriorating product which loses value while in the transportation stage [191], leads to the requirement that the logistics of the sugar supply chain be streamlined in order to ensure the survival of the industry. Indeed, there is currently a concerted effort in the industry to collaborate across busi- ness entity boundaries and with government [193]. For example, there is collaboration among growers with respect to co-owning logistical equipment [25] and collaboration between growers and millers concerning the implementation of computerised logistical scheduling systems [69]. In terms of computerised decision support for sugarcane estates, SQR Software’s CANEPRO system [199] supports the management of 130 000 hectares of land for several estates with re- spect to operational planning, manual agricultural activity scheduling, field data-basing and costing.
A farm of commercial proportions is ideally designed and managed to maximise land use, pro- viding fields that are fit for available cultivation and harvesting equipment as well as accessible by the relevant transportation vehicles, while minimising negative environmental impact such as erosion, wetland encroachment and flora and fauna habitat destruction [181,182]. One visible effect of the layout design is that farms are typically divided into fields, usually separated by relatively wide firebreaks, neighbouring fields often differing quite substantially in appearance from one another. These differences in appearance are not circumstantial; it is due to careful planning of cultivation stages, crop age1 and sugarcane variety interspersion, so as to minimise
the risks of runaway fires, insect infestation proliferation, the spread of fungal and other diseases as well as hampering hillside water run-off velocities during periods of heavy rainfall [182]. While layout design is an ongoing issue at the strategic farming level, one may argue that harvesting tacticsare in themselves crucial in maintaining a resilient and sustainable commercial sugarcane farm—both financially and environmentally. Even with a carefully planned layout, some fields may be connected by roads that are too steep to travel on or may themselves be too steep to allow harvesting during the rainy season. Figure 1.2 shows sugarcane harvesting in progress on a hillside. Other fields may be situated in an area that is exceptionally dry, experiences frost regularly or dries off slowly following rain. While considering such physical properties of the farm, it is equally important to be aware of any occasional minor disruption or major disaster that may strike the sugarcane. A frosted field, or one that has been overrun by accidental fire, may become a financial disaster if not tended to immediately, while a field that has had its sugarcane lodged (blown down) may only constitute a developing problem [182]. In South Africa, sugarcane is grown in cycles of twelve to twenty-four months. Different sugar- cane varieties display different seasonal sucrose content trends, which generally peak during the middle of winter [182]. Ideally, this is the time around which the entire farming strategy, layout design, sugarcane variety interspersion planning and harvesting tactics should be oriented. The tactical harvesting problem is, however, a more challenging reality since cane must be harvested at a consistent rate throughout the entire nine-month season, according to the rules and regula- tions governing the South African sugar industry. This is to spread out the workload, requiring
1
Figure 1.2: Hillside harvesting should preferably occur during dry conditions, since harvesting machin- ery tends to slide on wet, sloping earth. The topography of a farm is one of the factors to consider in tactical sugarcane harvest scheduling.
less milling capacity and thus save money.
A commercial sugarcane farm may comprise more than 120 fields, and most of the crops on these fields as well as the field properties themselves, are different from one another. These dif- ferences may be small when viewing them at an instant, but their effects typically become more distinguishable over time. When considering the number of different answers to the question of how to schedule the harvest of 120 different fields, the harvest scheduling problem seems a little daunting. Determining the harvest schedule is, however, at the centre of remediating the negative of the effects of the various disruptions and major disasters mentioned earlier and prof- iting from the positive of these effects; hence the challenge and value embedded in the tactical sugarcane harvest scheduling problem treated in this dissertation.
This dissertation contains an approach to modelling and solving the problem of providing com- puterised decision support to people charged with the task of scheduling the harvest of sugar- cane. The approach involves models of sugarcane growth, sugarcane deterioration when struck by disease, frost, insect infestations, fire and other adverse events. These models are then used to estimate the net profit from harvesting each field at each point in time into the future of a current season. Once each field has a net profit associated with its harvesting, an optimisation model is used to construct a schedule of maximum estimated profit, by ordering the fields in such a way as to maximise their combined net profit. This schedule is the proposed solution to the decision support problem described in this dissertation, and the focus is mainly on medium-scale commercial growers and groups of such growers working co-operatively.
1.3 Dissertation aim and objectives
This dissertation is aimed at advancing the current state of research on decision support systems (DSSs) for sugarcane harvest scheduling in South Africa. Towards realising this aim, nine detailed objectives are pursued throughout.
Objective I: To perform a literature survey of operations research models previously formu- lated in the context of optimising the sugar supply chain, the sugar supply chain’s indi- vidual parts from growing to the mill yard, and other supply chains that relate to the problem at hand.
Objective II: To perform a literature survey of related combinatorial optimisation problems and conventional solution methodologies in order to establish a foundation of scientifically
1.3. Dissertation aim and objectives 5 sound and practically suitable models and associated solution methods on which to base the core of the DSS put forward in this dissertation.
Objective III: To perform a literature survey of the methods previously and currently used to model sugarcane mass, value per unit of mass and harvesting costs in order to establish a foundation from which to develop a suitable methodology for predicting
a) sugarcane yield based on readily available data,
b) sugarcane relative recoverable value percentage based on readily available data, c) sugarcane harvesting costs based on readily available data.
Objective IV: To perform a literature survey and to interact with suitable role-players in the sugar industry in order to gain an understanding of the various factors that affect the growth, quality and survival of sugarcane crops, in order to establish a foundation on which to develop means of adjusting predictions of sugarcane yield, relative recoverable value percentage and harvesting costs, when such factors are in effect. Examples of these factors are foreseen to include, but are not limited to, accidental fire, frost of varying degrees, diseases, insect infestations and drought.
Objective V: To conduct an empirical combined evaluation and development experiment at the level of potential DSS users in order to determine what capabilities a tactical harvest scheduling DSS should possess and how those capabilities may be supported mathemati- cally, in order for such a DSS to be useful to the South African sugar industry.
Objective VI: To put forward a viable suggestion with respect to sugarcane crop harvesting decision support, based on the results of pursuing Objectives I–V, by
a) designing a generic DSS architecture so that it may accommodate relevant building blocks without loss of capability, showing its data requirements, how the data are transformed and flow within the DSS, as well as what processes utilise the data and how these processes are sequenced,
b) populate the DSS architecture with various building blocks, such as interfaces, data- bases, mathematical models, solution methodologies for these models and evaluation tools.
Objective VII: To render useful the DSS of Objective VI, by
a) implementing the DSS on a personal computer so as to achieve a stand-alone pro- gram which does not require specialist software to be installed for its execution and subsequent use,
b) testing and debugging the DSS implementation by means of a sequence of experiments interspersed with implementation corrections designed to render the DSS capable of performing consistently and predictably in practice.
Objective VIII: To validate the effectiveness of the DSS implementation of Objective VII, by a) shadow scheduling at least one actual harvesting operation for an entire season, while implementing newly found necessary or improving changes or additions to the various building blocks of the DSS,
b) drawing opinions from the industry representatives involved in a),
c) comparing actual harvesting schedules with the DSS-generated schedules as a means of benchmarking the DSS with respect to the decisions of industry professionals.
Objective IX: To outline ideas for future work and to provide possible directions in which to proceed in order to further advance the research on operations research-based DSSs for tactical sugarcane harvest scheduling in South Africa and other nations.
1.4 Dissertation scope
The methodology within the DSS for predicting cane yield2 for an undamaged, disease-free
cane crop not treated with chemical ripener3, not in a state of water stress, shall provide for the
employment of empirical models derived from data readily available to the user4, (such as field
records from a representative geographical area under representative agroclimatic5 conditions).
The DSS shall provide for the user to be able to manually adjust the predicted cane yield values field-by-field for perceived errors due to detailed conditions which are in this dissertation considered unpredictable. For example, such conditions may be unexplained low cane yield in a field which is apparently healthy, low cane yield in a field due to crop class6 (when data are
not sufficient for incorporating the factor crop class into the prediction models) or generally different than expected cane yield in some field due to other factors that were not modelled explicitly when applying the methodology for predicting cane yield on the available data. The methodology within the DSS for predicting cane recoverable value percentage7 (RV %)
shall be subject to the same limitations and provision requirements as the methodology within the DSS for predicting cane yield, insofar as these limitations and provisions bear meaningful implications, except for the provision that the user may manually adjust cane yield estimates, but not cane recoverable value percentage estimates.
The DSS shall accommodate the incorporation, by the user of the DSS, of alternative models for predicting the effects of extraneous events8 that may impact substantially on the value or
future value of cane crops9, and in particular their effects on cane yield and cane recoverable
value percentage as functions of time (since the occurrence of the event).
The DSS shall take into consideration to a reasonable level the differences in harvesting costs which arise due to varying field properties and weather. It shall be possible for the user to
2
The term cane is taken throughout this dissertation to mean sugarcane. The term cane yield is taken throughout this dissertation to mean the mass of cane, including the sucrose and other components, and is thus a production quantity. The term cane yield per hectare is taken to mean the mass of cane per hectare and is thus a measure of productivity.
3A chemical ripener is a chemical that, when applied to unstressed sugarcane, may increase the amount of
sugar in the cane stalks as well as the purity of the juices within the cane stalks [38].
4The term user is taken throughout this dissertation to mean a person who knows how to use the DSS put
forward in this dissertation.
5
The term agroclimatic is used throughout this dissertation to mean temperature, incident solar radiation, rainfall and wind conditions; climatic factors that are known to influence agriculture [18].
6
The term crop class refers to the number of times that a cane field has been harvested since it was planted. A crop class of 0 is called a plant crop and a crop class of 1 means that the crop has re-germinated from the root system of a plant crop after initially being harvested, such a crop is also called a ratoon.
7The term cane recoverable value percentage means the percentage of the cane yield of a crop for which the
seller of the crop receives payment, after the affixation of a market and regulation-dependent recoverable value price [195].
8
The term extraneous event is taken throughout this dissertation to mean an event, which may occur on or inside the cane roots, stalks or leaves as well as in a crop or field as a whole, and which is known to alter the normal growth or normal quality of the crop positively or negatively.
9
The term crop is taken throughout this dissertation to mean the sugarcane present in a single field. The term field is therefore equivalent to the term crop when referring to the sugarcane, but the term field is more appropriate when referring to the field as part of the layout of the farm.
1.5. Dissertation structure 7 adjust these considerations to fit his/her situation.
The DSS shall be designed and validated for South African conditions, for geographical and agro- climatic regions where sugarcane crops are harvested approximately every twenty-two months and do not require extensive irrigation.
Furthermore, the DSS is to be designed for medium-scale growers and co-operative joint ventures between such growers, but is hoped to apply to other types of sugarcane harvesting contexts as well.
1.5 Dissertation structure
This dissertation comprises three parts: a part on previous work by researchers related to sugarcane production leading up to a formal problem description, a part dedicated to describing the solution to the problem and finally a part devoted to summarising the dissertation and presenting a few proposals for future research.
Part I consists of Chapters 2, 3 and 4. Chapter 2 contains a brief review of the literature on previous work employing operations research-based methods on modelling sugarcane flow, a very brief review of current research in the field of supply chain management and a brief review of value chain research on agricultural value chains. Moreover, Chapter 2 contains an effort to organise previous results on how sugarcane deteriorates when having been subjected to various extraneous events, and is in particular devoted to a thorough study of authoritative information