(104h) Identifying the Preferred Subset of Alternatives for Environmental Improvements Via an MILP Approach Based on the Analytic Hierarchy Process
AIChE Annual Meeting
2014
2014 AIChE Annual Meeting
Environmental Division
Advances in Life Cycle Optimization for Process Development
Monday, November 17, 2014 - 2:29pm to 2:46pm
The combined use of multi-objective optimization (MOO) and LCA has recently gained wider interest in process systems engineering. This approach provides as output a set of Pareto solutions that represent the optimal trade-off between the economic and environmental concerns considered in the analysis. From this set of optimal alternatives, decision-makers should identify the ones that better fulfill their preferences. Generating a large and representative enough subset of Pareto points to aid decision-making is challenging. This task is particularly difficult in problems with a large number of (environmental) objectives, as is the case when incorporating LCA principles in MOO.
In this work we present a mixed-integer linear programming method that simplifies MOO problems by concentrating on determining only a reduced number of Pareto points that are particularly appealing. Our approach, which relies on the analytic hierarchy process (AHP), identifies a set of weights to be assigned to the environmental objectives so as to translate them into a single aggregated indicator that reflects to the maximum extent possible the decision-makers' preferences. For every such combination of weights, we solve a single objective problem that optimizes the corresponding weighted sum of objectives, thereby generating only a subset of alternatives (Pareto solutions) reflecting preferences with a large degree of consistency. We illustrate the capabilities of our approach through its application to the design of supply chains for bioethanol production.