Abstract
In this paper, we analyse a complex production planning problem in a Make-To-Order company, involving quoting due dates, along with production scheduling, some plant layout decisions and line balancing issues. A general framework has been developed that identifies the main levels for decision making, and tackles these problems in a hierarchical fashion, the resulting interactions being carefully taken into consideration. This framework, based on considering discretised planning horizons, is implemented on a Decision Support System developed around an interface specially designed to involve the various participants in the planning process. In practice, the system is composed by a package of software products used as add-ons to the main management information system of the company. A comprehensive and detailed description of the approach, techniques used and developed algorithms is presented. The experience in using a first prototype of the system shows this may become a highly valuable computer tool in production planning, layout design and assignment of orders.

Abstract
The process of monitoring the machines or computing nodes in a network, and of monitoring the communication traffic between them, is very important to efficiently launch and execute parallel coarse-grained applications or even classical (serial-type) applications, taking advantage of machines in the network that are not heavily used. An experimental software system, named MONSYS, that is capable of monitoring the machines in a network, is presented. MONSYS can be used in the support of an Application Manager system capable of distributing parallel tasks (or classical programs) over the machines in a local area network with the objective of achieving load balancing. It can also be used as a tool in the administration of networks. MONSYS exhibits a highly decentralized and fault tolerant architecture based on the Peer-Model, which, together with its information diffusion algorithms, constitute its prime novelty. A set of experiments that investigate the performance and scalability of a prototype of MONSYS is presented and discussed. The experiments reported show that MONSYS offers a reasonably accurate picture of the internal state of the machines monitored, without being a burden to the network communication channels or to the machines themselves. In fact, the quantitative results obtained indicate that MONSYS can be several times more performant than an equivalent system using a multicast communication scheme for the exchange of machine state information.

Abstract
This paper addresses the problem of buying commodities through the futures markets and deals specifically with a heuristic rule developed for the scenario described as ‘purchasing under a deadline’. The rule is based on a short-term forecasts produced by Taylor’s price-trend model. In a previous study applied to the Chicago Board of Trade (CBOT) corn futures market the price-trend parameters of the stochastic process generating the daily returns were shown to be nearly stable over time and hence could be estimated using a static procedure. However, the analysis presented in this paper concerning the CBOT soybean futures market strongly suggests that those parameters were unstable, impairing the successful application of the purchasing rule. The authors recommend the continuous CUSUM monitoring of the purchasing results and propose a procedure for dynamically calibrating the price-trend and buying parameters. Under this procedure the price-trend parameter estimates are derived from exponentially smoothed sample autocorrelation coefficients of the rescaled daily returns. The procedure was developed and tested using the 1972-87 series of CBOT daily soybean futures closing prices. The results suggest that it leads to an improvement on the purchasing results derived from the static parameter calibration procedure formerly adopted. © 1994 Operational Research Society Ltd.

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