Optimizing returns from forest estates and from wood processing industries in Tanzania using linear programming

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dc.contributor.authorKowero, Godwin Sifueli
dc.date.accessioned2016-05-09T01:24:23Z
dc.date.accessioned2020-01-07T13:36:14Z
dc.date.available2016-05-09T01:24:23Z
dc.date.available2020-01-07T13:36:14Z
dc.date.issued1983
dc.descriptionAvailable in print form, East Africana Collection, Dr. Wilbert Chagula Library, Class mark (THS WRE TD365.J67)en_US
dc.description.abstractThe forest policy of Tanzania provides far two optimization objectives: (a) to manage the forest estate in such a manner as to make it as productive as possible; and (b} to utilize forest produce from public lands to the best advantage of the community. This study was undertaken in an effort to develop a comprehensive methodology to assist both managers of forest projects and managers of wood processing facilities to manage their operations so that these objectives can be satisfied. In order to determine the degree to which the objectives are being fulfilled at present, case studies were made of the Meru Forest Project (MFP) and a wood processing complex, Fibreboard Africa Ltd. (FAL). Both are located in Arusha Region in northern Tanzania. The methodology developed in this study to improve decisions relating to forest operations and wood processing operations makes use of linear programming. Two independent linear progamming (LP) models were developed: the general processing model (GPM), based on the wood processing facility, and the plantation model (PM), and based on the forest project. Since Fibreboard Africa Ltd. is the major customer of the Meru F Forest ' Project, and the forest project is the major supplier of wood raw materials to this processing complex, it was also possible to .link the two models into a limited model of the forestry sector in that region. This is called the miniforestry sector medal (MF5M). The results of the GPM revealed superiority, in various ways, of this LP model over current planning techniques at FAL. For example, in addition to providing very valuable economic information in the process of its formulation, the GPM solutions identify different wood raw material combinations which FAL can use to manufacture specified product combinations. As an example, one of the most suitable alternative solutions for implementation, alternative one, indicates that 17% of FAL's hardboard mill wood raw material should be obtained from FA sawmill residues, with the remaining 83% being supplied by MFP.On implementing the production programme identified for alternative one, FAL would earn estimated annual net revenue of shs 24.6 million. This would make FAL a profitable enterprise for the first time since it became operational ten years ago. These revenue earnings are, however, based on two basic assumptions. First, FAL would have to be fully operational without major disruptions resulting from technical constraints. In addition, FAL would require an annual recurrent expenditure of shs.16.4 million, a level of funding which is not very different: from that ob erved from the previous .years. The results from the PM indicated that MFP could, if it implements these results, earn a net revenue of she. 25.61 million in the first five year period, assuming that MFP level of funding would continue at levels not significantly different from those observed during the past three years: In addition, such revenues would be earned by harvesting only 57.6% of the harvest volume scheduled in the managemeet plan for the same period. Current projections by MFP indicate forecasted earnings of shs.25.15 million during this period, or 2% less than that achievable by the PM solution on a much lower harvest volume. This is because of the superiority of PM in selecting the mix of species and age classes to harvest on the basis of a financial optimality criterion, as compared to intuitive guidelines pursued by the management of MFP. The results from the MFSM indicated that net earnings to MFP would decline to shs.`15.87 million in the first five year plan period as compared to the PM solution. Net revenues to the industries remained at the levels in the GPM solution, implying that wood raw material supply to these industries is not a binding constraint at their current levels of capacity utilization. This indicates that MFP cannot sell all its produce to FAL. It can only sell up to the level of demand, which is limited not only by the installed capacity but more by the low level of actual capacity utilization, which was less than 30% for all FAL units except the sawm ll which operated at 60% capacity utilization. As a result, the decline in revenues to MFP should be interpreted as resulting from the inability of the mills to consume more wood from the forest either due to technical or financial constraints. Therefore MFP will operate according to the MFSM results and not according to the PM results. It can be concluded that MFP's revenue projections are overly optimistic because of limitations imposed by installed capacity and the level of capacity utilization presently attained at the mills. This indicates rather conclusively that investments in the immediate future should concentrate on the expansion of the wood processing capacity in this region rather than on the expansion of the forest estate. Also, the study indicates that LP can be used successfully to improve decisions relating to the management of both forest operations and wood processing operations. In doing so, LP fulfills the two optimizing objectives stated in Tanzania's forest policy directive. However, these decisions cannot be taken independently but must be connected through the wood raw material link that exists in common between them.en_US
dc.identifier.citationKowero, G. S.(1983) Optimizing returns from forest estates and from wood processing industries in Tanzania using linear programming, PhD dissertation, University of Dar es Salaam. Available at (http://41.86.178.3/internetserver3.1.2/detail.aspx?parentpriref=)en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/131
dc.language.isoenen_US
dc.publisherUniversity of Dar es Salaamen_US
dc.subjectForest and forestryen_US
dc.subjectEconomic aspectsen_US
dc.subjectWood working industriesen_US
dc.subjectForest policyen_US
dc.subjectTanzaniaen_US
dc.titleOptimizing returns from forest estates and from wood processing industries in Tanzania using linear programmingen_US
dc.typeThesisen_US
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