20 th European Symposium on Computer Aided Process Engineering – ESCAPE20 S. Pierucci and G. Buzzi Ferraris (Editors) © 2010 Elsevier B.V. All rights reserved. Fuzzy-like Optimization Approach for Design and Scheduling of Multipurpose Non-Periodic Facilities Tânia Pinto-Varela §1,2 , Ana Paula F. D. Barbósa-Póvoa 2 and Augusto Q. Novais 1 1 Unidade de Modelação e Optimização de Sistemas Energéticos (former Departamento 11de Modelação e Optimização of INETI), LNEG, Lisboa, Portugal 2 Centro de Estudos de Gestão do IST, UTL, Lisboa, Portugal Abstract This paper deals with the design and scheduling optimization of multipurpose non- periodic facilities, considering three different approaches to solve the conflicting objectives often present in this type of problems. Like in most facilities, this problem involves the maximization of the total revenue as well as the minimization of the total cost. The best way to deal with these two goals simultaneously is either to combine them into a single criterion (e.g., profit) or to apply a multi-objective optimization approach, although the latter may become very lengthy with the increase of the problem complexity. In this work we present an alternative optimization approach, adapted from symmetric fuzzy linear programming (SFLP), which is applied to the design and scheduling of this kind of facilities. An example is used to show the methodology application and results are compared to those located on the efficient frontier, which were obtained with the mono-objective model through the ε-constraint approach. Keywords: Scheduling, Design, Multi-objective, Fuzzy. 1. Introduction In multipurpose batch facilities, a wide variety of products can be produced via different processing recipes through the sharing of available resources, such as equipment, raw and intermediate materials, and utilities. The design of multipurpose batch facilities, real-world problems alike, involves multiples objectives, but most of the existing literature on their design has been centred on mono-criterion objectives (Barbosa- Povoa, 2007). There is therefore considerable scope for further investigation into the multi-objective optimization of such facilities. Dietz et al. (2006) presented a multi- objective cost-environment design of multiproduct batch plants. The approach used consists in coupling a stochastic algorithm, defined as a genetic algorithm, with a discrete event simulator. A multi-objective genetic algorithm was developed with a Pareto optimal ranking method. The same author proposed the problem of the optimal design of batch plants with imprecise demands using fuzzy concepts (Dietz, 2008) where the multi-objective problem was extended to take into account simultaneously maximization of the net value and two performance criteria, i.e., the production delay/advance and flexibility. Aguilar-Lasserre et al. (2009) addressed the problem of  Author to whom all correspondence should be addressed. E-mail: tania.pinto@ineti.pt