Howell, "Multiple-Goal Objective Functions for Optimization of Task Assignment in Computer Systems," Elsevier, Control Engineering Practice, Vol. 4, Iss. 2, February 1996. Earlier version: PToc. 19 th IFAC/IFIP
Multiobjective optimization is minimizing or maximizing multiple objective functions subject to a set of constraints. Example problems include analyzing design tradeoffs, selecting optimal product or process designs, or any other application where you need an optimal solution with tradeoffs between two or ...
For this purpose, multiobjective optimization techniques may be used. In a multiobjective optimization problem,46–49 multiple objective functions F1(u), F2(u), …, Fn(u) must be simultaneously maximized or minimized (or a combination of both) with respect to vector u. In the variable ...
在具有偏好先验信息的求解方法中,还有边界目标函数法(bounded objective function method)以及物理规划(physical programming)等方法。 2.2 具有偏好后验表达的方法 在某些情况下,决策者很难明确表示出偏好函数。同时,通过改变权重以重复求解加权效用函数,可能无法提供均匀分布的点,从而准确地表示完全帕累托最优集。此外,...
Lemma 3.5(Convexity)If all objective functions{f1(x),⋯,fm(x)}are convex, then the STCH scalarizationgμSTCH(x∣λ)with any validμandλis convex. Proposition 3.6(Iteration Complexity)If all objective fuctions are convex, with a properly chosen smoothing parameterμ, we can obtain anϵ...
Multiobjective optimizationcaters to achieving multiple goals, subject to a set of constraints, with a likelihood that the objectives will conflict with each other. Multiobjective optimization can also be explained as a multicriteria decision-making process, in which multiple objective functions have to...
are connected both in objective space and parameter space. Besides, the Pareto-optimal solutions often dis- tribute so regularly in parameter space that they can be defined by piecewise linear functions. By constructing an approximate model using the solutions produced by ...
The survey analyzes separately the cases of two objective functions, and the case with a number of objective functions strictly greater than two. More than 50 references on the topic have been reported. Another interesting survey on these techniques related to multiple objective integer programming ...
3.1 Method of Objective Weighting This is probably the simplest of all classical techniques. Multiple objective functions are combined into one overall objective function, Z , as follows: PN Z = i=1 wi fi (x); (2) where x 2 X; X{ the feasible region; the weights wi are fractional ...
Normally, in multiobjective optimization problems, multiple objective functions are converted to a single objective function for which different strategies are employed. However, any multiobjective optimization algorithm performs two tasks. The first task is to find a solution that decides the limits of...