Abstract
This paper presents a reference position on the relation between manufacturing systems and work organisation strategies, It raises some issues and advances a methodological framework in the development of information/manufacturing systems and work organisation design methods. as to reach a balanced influence of the technology, organisation and people aspects in Complex Manufacturing Environments (CME). In this sense it is not presenting research results but, with the underlying goal of implementing a laboratory environment for the study of technical and or organisational developmental aspects of CMEs, there are overviewed the R&D requirements for an interdisciplinary approach involving Computer and Social Sciences. The main scientific areas analysed are Enterprise Integration and Work Organisation, focusing on the methodological aspects of each one.

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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.

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We consider the formulation of non-preemptive single machine scheduling problems using time-indexed variables. This approach leads to very large models, but gives better lower bounds than other mixed integer programming formulations. We derive a variety of valid inequalities, and show the role of constraint aggregation and the knapsack problem with generalised upper bound constraints as a way of generating such inequalities. A cutting plane/branch-and-bound algorithm based on these inequalities has been implemented. Computational experience on small problems with 20/30 jobs and various constraints and objective functions is presented.