This paper reviews a series of environmental indicators developed in the last years that were found suitable to be applied at corporate level for the evaluation of production processes and products. The indicators reviewed in this paper were classified into four main groups: 1) Indicators of Energy and Material Flows; 2) Indicators with a Territorial Dimension; 3) Indicators of Life-Cycle Assessment; 4) Indicators of Environmental Risk Assessment. Integrative and single index indicators such as the ecological footprint or carbon footprint were found as the most appealing for enterprises, although there is a need to advance in the field to combine the simplicity required at corporate level for tracking and reporting environmental data, and the scientific rigor and transparency necessary to make the scores reliable. Hence, for each of the indicators revised it was stated what they do and do not measure so that misleading information was not used for decision making at corporate level.

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A fuzzy-based expert system (ES) for the diagnosis and supervision for anaerobic digesters is presented. The system was developed in a Microsoft Windows support using fuzzy logic inference together with a rule base for the implementation of expert knowledge. The ES runs on-line through three main modules, which determine the state and trend of the process, and the best set points for the actuation on the final control elements of the plant. Two further modules run in parallel, when they are required by the operator, using off-line and on-line information for the detection of inhibition due to toxic compounds in the process and for the validation of the on-line diagnosis. The diagnosis and supervision ES was tuned up in order to adjust the membership functions describing the process, and lately tested, running on-line, to study the response of the rule base.

The dynamic optimization (optimal control) of chemical batch reactors is considered. The solution of these types of problems is usually very difficult due to their highly nonlinear and multimodal nature. In fact, although several deterministic techniques have been proposed to solve these problems, convergence difficulties have been frequently found. Here, two algorithms based on stochastic optimization are proposed as reliable alternatives. These stochastic algorithms are used to succesfully solve four difficult case studies taken from the recent literature:  the Denbigh's system of reactions, the oil shale pyrolysis problem, the optimal fed-batch control of induced foreign protein production by recombinant bacteria, and the optimal drug scheduling of cancer chemotherapy. The advantages of these alternative techniques, including ease of implementation, global convergence properties, and good computational efficiency, are discussed.

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