Group decision as a twice multicriteria optimum problem

This paper studies the problem of aggregation of preferences, preserving the multicriteria nature of the individual decision process. The resulting group decision problem is in effect a twice multicriteria optimum problem. We give a structural theory for the efficient set of this optimum problem. Moreover, on the basis of this theory we study the relationships between optimality, consensus and evaluation. We confirm the pathological nature of aggregation of preferences, but in a new setting and with a different meaning.     

Some Remarks on Dualization in Vector Optimization

In recent years there have been several reports on duality in vector optimization. However, there seems to be no unified approach to dualization. In a previous paper by the author a geometric consideration was given to duality in non-linear vector optimization. In this paper a relationship between duality, stability (normality) and condition of the alternative will be reported on the basis of some geometric consideration. In addition, Iserman's duality in linear cases will be derived from the stated geometric approach.     

异步异构分层并行演化算法及其在串并系统可靠性优化中的应用(英文)

本文提出了一种新的并行演化算法――异步异构分层并行演化算法(AHHPGA),用于求解串并系统可靠性分配的多目标优化问题(RAP)。AHHPGA采用分层结构,上层由粗粒度模型构成,下层由细粒度模型构成。在AHHPGA的每个子种群中,采用不同的全局/局部搜索度和拓扑结构,构成异构模型。AHHPGA的迁移方式包括异步接收和异步迁出。采用基于模型的复杂系统可靠性评价工具(HiP-HOPS),以克服可靠性框图方法(RBD)的缺点。仿真结果表明,基于异步异构分层并行演化算法和HiP-HOPS工具的串并系统可靠性分配的多目标优化方法,优于传统的基于遗传算法的优化方法。     

Multiobjective optimization for interwoven systems

In practical situations, complex systems are often composed of subsystems or subproblems with single or multiple objectives. These subsystems focus on different aspects of the overall system, but they often have strong interactions with each other and they are usually not sequentially ordered or obviously decomposable. Thus, the individual solutions of subproblems do not generally induce a solution for the overall system. Here, we strive to identify “re‐composition architectures” of such “interwoven” systems. Our intention is to connect the subsystems adequately, analyze the resulting performance, model/solve the overall system, and improve the overall solution instead of just solving each subsystem separately. We review recent developments in this field and discuss modeling and solution paradigms in a general and unified framework using the example of an interwoven system consisting of two interacting subsystems.