Sustainable production technologies which take into account environmental constraints

We formulate and study a multiobjective programming approach for production processes which implements suitable constraints on pollutant emissions. We consider two alternative optimization problems: (a) minimum pollution risk; (b) maximum expected return. For each pollutant, we define three different contamination levels: (a) the desirable or the target pollution level, (b) the alarm (warning or critical) level and (c) the maximum admissible (acceptable) level, and introduce penalties proportional to the amounts of pollutants that exceed these levels. The objective function of the minimum pollution risk problem is not smooth since it contains positive parts of some affine functions, resulting in mathematical difficulties, which can be solved by formulating an alternative linear programming model, which makes use of additional variables and has the same solutions as the initial problem. We investigate various particular cases and analyze a numerical example for a textile plant.