It has been empirically established that multiobjective evolutionary algorithms do not scale well with the number of conflicting objectives. This paper shows that the convergence rate of all comparison-based multi-objective algorithms, for the Hausdorff distance, is not much better than the convergence rate of the random search under certain conditions. The number of objectives must be very mod...

A bi-criteria optimization is considered whose objectives are the maximization of the load sustained by a structure and the minimization of the structure's volume. As the objectives are conflicting, the solution to the problem is of the Pareto type. The problem is elaborated for a thin-walled column of cruciform cross-section, prone to flexural and torsional buckling. A numerical example is als...

In the portfolio selection problem, the manager considers several objectives simultaneously such as the rate of return, the liquidity and the risk of portfolios. These objectives are conflicting and incommensurable. Moreover, the objectives can be imprecise. Generally, the portfolio manager seeks the best combination of the stocks that meets his investment objectives. The imprecise Goal Program...

It is shown that in the case of a single decision maker who optimizes several possibly conflicting objectives, the amount of information available in preference relations among pairs of possible decisions, when compared with all other possible information, is tending to zero exponentially with the number of those different objectives. Consequently, in the case of a larger number of conflicting ...

It is argued that to achieve the required balance between objectives, a scheduling system must have the ability to relate the consequence of a decision to the satisfaction of overall objectives. The dissertation introduces the concept of a preference capacity plan (PCP) in an attempt to give automated schedulers this ability. PCP takes cognizance of both predicted demand for capacity and the in...

UK military commanders have a degree of devolved decision authority delegated from command and control (C2) regulators, and they are trained and expected to act rationally and accountably. Therefore from a Bayesian perspective they should be subjective expected utility maximizers. In fact they largely appear to be so. However when current tactical objectives con‡ict with broader campaign object...

Smart agents are equipped with sensors that enable them to be sensitive to their surrounding environment. However, the mapping of multiple raw streams of sensory data to the appropriate actions is not an easy problem, especially when multiple conflicting objectives are involved. This type of multi-sensor fusion problem through the domain of power management for smart mobile devices was investig...

Here P is the plant system concerned, C is the controller and the signal r, y, a, u and n are the reference, system output, control input, output disturbance and sensor noise respectively. Classical control systems design emphasizes the securing of a number of conflicting objectives for this feedback system such as; . securing closed loop stability from each external input to the loop signals u...

A solution methodology for the design of digital infinite impulse response (IIR) filter considering multiple conflicting objectives has been proposed. The nucleus of the method is that multiple objectives can be attuned suitably, to optimize the performance in pass bands, stop bands and transition bands of IIR digital filters. The proposed method uses multiobjective optimization approach for de...