often in modeling the engineering optimization design problems, the value of objective function(s) is not clearly defined in terms of design variables. instead it is obtained by some numerical analysis such as fe structural analysis, fluid mechanic analysis, and thermodynamic analysis, etc. yet, the numerical analyses are considerably time consuming to obtain the final value of objective functi...

The multiobjective bilevel program is a sequence of two optimization problems, with the upper-level problem being multiobjective and the constraint region of the upper level problem being determined implicitly by the solution set to the lower-level problem. In the case where the Karush-Kuhn-Tucker (KKT) condition is necessary and sufficient for global optimality of all lower-level problems near...

In multiobjective optimisation, one of the most common ways of describing the decision makerÕs preferences is to assign targeted values (goals) to con ̄icting objectives as well as relative weights and priority levels for attaining the goals. In linear and convex decision situations, traditional goal programming provides a pragmatic and ̄exible manner to cater for the above preferences. In certa...

In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. The optimal VAR dispatch problem is formulated as a nonlinear constrained multiobjective optimization problem where the real power loss and the bus voltage deviations are to be minimized simultaneously. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is...

Static and dynamic multiobjective topology optimization of trusses with interval parameters is investigated. The uncertain parameters of the trusses are described by an interval model. The multiobjective topology optimization model of trusses with interval parameters is constructed. On the basis of Taylor expansion and natural interval extension, the stress and displacement response intervals u...

In this study, a problem space genetic algorithm (PSGA) is used to solve bicriteria tool management and scheduling problems simultaneously in ¯exible manufacturing systems. The PSGA is used to generate approximately ef®cient solutions minimizing both the manufacturing cost and total weighted tardiness. This is the ®rst implementation of PSGA to solve a multiobjective optimization problem (MOP)....

Mobile Ad-hoc Networks (MANETs) are composed of a set of communicating devices which are able to spontaneously interconnect without any pre-existing infrastructure. In such scenario, broadcasting becomes an operation of capital importance for the own existence and operation of the network. Optimizing a broadcasting strategy in MANETs is a multiobjective problem accounting for three goals: reach...

This thesis proposes a new necessary condition for the infeasibility of non-linear optimization problems (that becomes necessary under convexity assumption) which is stated as a Pareto-criticality condition of an auxiliary multiobjective optimization problem. This condition can be evaluated, in a given problem, using multiobjective optimization algorithms, in a search that either leads to a fea...

Ridesharing is considered as one of the promising solutions for dropping the consumption of fuel and reducing the congestion in urban cities, hence reducing the environmental pollution. Route planning is a key component for the success of ridesharing systems in which multiple objectives can be optimized. The multiobjective route planning problem in multi-hop ridesharing is categorized as NP–com...

Until recently, optimization was regarded as a discipline of rather theoretical interest, with limited real-life applicability due to the computational or experimental expense involved. Multiobjective optimization was considered as a utopia even in academic studies due to the multiplication of this expense. This paper discusses the idea of using surrogate models for multiobjective optimization....