The multicriteria decision process consists of five main steps: definition of the optimisation problem, determination of the weight structure of the decision criteria, design of the evaluation matrix, selection of the optimal evaluation method and ranking of solutions. It is often difficult to obtain the optimal solution to a multicriterion problem. The main reason is the subjective element of the model – the weight functions of the decision criteria. Expert opinions are usually taken into account in their determination. The aim of this article is to present a novel method of minimizing the uncertainty of the weights of the decision criteria using Monte Carlo simulation and method of data reconciliation. The proposed method is illustrated by the example of multicriterion social effectiveness evaluation for electric power supply to a building using renewable energy sources.
In the paper an approach to decision making in situations with non-point-like characterisation and subjective evaluation of the actions is considered. The decision situation is represented mathematically as fuzzy multiobjective linear programming (fMOLP) model, where we apply the reduced fuzzy matrices instead of fuzzy classical numbers. The fMOLP model with reduced parameters is decomposable into the set of point-like models and the point-like models enable effective construction of an optimisation procedure – fBIP, see Wojewnik (2006ab), extending the bireference procedure by Michalowski and Szapiro (1992). The approach is applied to a fuzzy optimization problem in the area of telecommunication services.
The paper presents optimization of 5-rod (5-link) suspension mechanism used in passenger cars for independent guiding of the wheels. Selected stiffness coefficients defined for five elastomeric bushings installed in joints of the suspension rods are considered as design variables. Two models with lumped parameters (i.e. elastokinematic and dynamic) of wheel-suspension-car body system are formulated to describe relationships between the design variables and the performance indexes including car active safety and ride comfort, respectively. The multi-criteria goal function is minimized using a deterministic algorithm. The suspension with optimized bushings rates fulfils desired elastokinematic criteria together with a defined dynamic criterion, describing the so-called rolling comfort. An event of car passing over short road bump is considered as dynamic conditions. The numerical example deals with an actual middle-class passenger car with 5-rod suspension at the front driven axle. Estimation of the models parameters and their verification were carried out on the basis of indoor and outdoor experiments. The proposed optimization procedure can be used to improve the suspension design or development cycle.