Fuzzy Multi-objective Optimization of a Synthesis Unit Utilizing Uncertain Data

In any manufacturing system, the cost is considered to be the most significant factor and the reliability of any industrial system is also an increasingly important issue. On the other hand the available information about the constituent components of the system is most of the time imprecise, incomplete, vague and conflicting and the management decisions are based on experience. So it is very difficult to analyze their behavior and to predict their failure pattern. In such situations the decision making is difficult and the presence of multi-objectives gives rise to multi-objective optimization problem which leads to Pareto optimal solutions instead of single optimal solution. The objective of this paper is to quantify the uncertainties that makes the decision more realistic, generic and extendable to application domain. This paper deals the fuzzy multi-objective reliability optimization problem for synthesis unit of a complex configuration urea fertilizer plant where reliability and cost of the system are involved as conflicting objectives. By taking into account the DM/system expert preferences in the form of weights and the objectives’ membership functions, the problem is formulated as a single objective optimization problem and then solved with the particle swarm optimization. c ⃝2013 World Academic Press, UK. All rights reserved.