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Scheduling deteriorating jobs on parallel machines is an NP-hard problem, for which heuristics would be the ® rst solution option. Two variants of linearly deteriorating jobs are considered. The ® rst is that with simple linear deterioration, i.e. where there is a deterioration rate only, which is meaningful only if the jobs are assumed to be available at a positive time t 0 . In the second variant, there is a basic processing time and a deterioration rate and all jobs are available at time t ˆ0. In both cases, we seek to minimize the makespan.Starting from simple heuristics, both steepest descent search and simulated annealing are designed and implemented to arrive at optimal or near-optimal solutions.Computational results for randomly generated problem instances with diå erent job/machine combinations are presented.

operation, yet plant design optimisation decisions are based on past experience and intuition rather than on scientific analysis. Genetic algorithms as a tool for circuit analysis in plant design and optimisation was considered. The multi-objective evolutionary algorithm initialises the plant design and optimisation based on experimental results, which are used to formulate and determine the objective function values. A simulation was conducted to assess the performance of candidate solutions. The two optima are then traded-off using cost objective, which is sought to be minimized. Once an optimum was selected, the circuit mass balance and equipment design was performed, bringing the theory of network design and genetic algorithms into unison. Results of the study provide financial benefits, optimal parameter settings for the comminution equipment and ultimately better plant performance.

Many of the production costs for producing tea are attributable to the process of drying the tea. E-manufacturing can assist companies to reduce these production costs by making crucial information available to decision-makers so that they can make informed decisions. This paper presents an application of e-manufacturing to the design of an automatic tea drying control system. This control system will ensure that the multiple drying parameters such as temperature, dryer-exit tea moisture content, and fuel consumption are maintained at optimal states during the course of the drying of tea. The additional aim of this system is to balance the cost of production and the quality of the final product. Using the Guggenheim-Anderson-De Boer (GAB) model, the optimum drying temperature was found to be 100-110°C, while maintaining a dryer-exit tea moisture content of 3 to 3.12 per cent, at a drying rate of 3 per cent per minute. A Barix control application to control the system's activities, using the web user interface (WUI), was also developed. OPSOMMING'n Groot gedeelte van die koste in die produksie van tee is as gevolg van die teedroogproses. E-vervaardiging kan die produksiekoste verminder deur kritiese inligting vir die besluitnemers beskikbaar te stel. Hierdie studie beskryf 'n toepassing van e-vervaardiging op die ontwerp van 'n outomatiese tee-droog beheerstelsel. Die beheerstelsel verseker dat al die droogparameters, soos temperatuur, voggehalte en brandstofverbruik, by optimum toestande beheer word deur die loop van die droogproses. Verder word daar deur die beheerstelsel 'n balans tussen die produksiekoste en die gehalte van die finale produk gehandhaaf. Deur van die Guggenheim-Anderson-De Boer (GAB) model gebruik te maak, is die optimale droogtemperatuur gevind om tussen 100 tot 110°C te lê, terwyl die droëruitlaatvoggehalte tussen 3 en 3.12% met 'n droogtempo van 3% per minuut te lê. 'n Barix beheer program is ontwikkel om die beheerstelsel se werksaamhede te monitor.2 The paper was written in support of L. Nyanga's PhD research on the development of an emanufacturing model for the South African industry.

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