Multiobjective evolutionary algorithms have incorporated surrogate models in order to reduce the number of required evaluations to approximate the Pareto front of computationally expensive multiobjective optimization problems. Currently, few works have reviewed the state of the art in this topic. However, the existing reviews have focused on classifying the evolutionary multiobjective optimizat...

Recently, a new iterative optimization framework utilizing an evolutionary algorithm called ”Prototype Optimization with Evolved iMprovement Steps” (POEMS) was introduced, which showed good performance on hard optimization problems large instances of TSP and real-valued optimization problems. Especially, on discrete optimization problems such as the TSP the algorithm exhibited much better searc...

Multiobjective combinatorial optimization problems are known to be hard problems for two reasons: their decision versions are often NPcomplete and they are often intractable. Apart from this general observation, are there also variants or cases of multiobjective combinatorial optimization problems which are easy and, if so, what causes them to be easy? This article is a first attempt to provide...

In practical applications it is common to have several conflicting objective functions to optimize. Frequently, these functions are nondifferentiable or discontinuous, could be subject to numerical noise and/or be of black-box type, preventing the use of derivative-based techniques. In this paper we give an overview of some recent developments in Derivative-free Multiobjective Optimization. We ...

This paper deals with multiobjective optimization techniques for a class of hybrid optimal control problems in mechanical systems. We deal with general nonlinear hybrid control systems described by boundary-value problems associated with hybrid-type Euler-Lagrange or Hamilton equations. The variational structure of the corresponding solutions makes it possible to reduce the original “mechanical...

Transportation plays a vital role in the development of a country and the car is the most commonly used means. However, in third world countries long waiting time for public buses is a common problem, especially when people need to switch buses. The problem becomes critical when one considers buses joining different villages and cities. Theoretically this problem can be solved by assigning more...

In this paper, the Simulated Evolution algorithm (SimE) is engineered to solve the optimization problem of multi-objective VLSI netlist bi-partitioning. The multi-objective version of the problem is addressed in which, power dissipation, timing performance, as well as cut-set are optimized while Balance is taken as a constraint. Fuzzy rules are used in order to design the overall multiobjective...

In this paper, we present an application of intuitionistic fuzzy optimization model to a two person multiobjective bi-matrix games (pair of pay-offs matrices) for the Nash equilibrium solution(NES) with mixed strategies. We use linear membership and non-membership function for such computation. We introduce the intuitionistic fuzzy(IF) goal for a choice of a strategy in a pay-off matrix in orde...

Many water resources systems are characterized by multiple objectives. For multiobjective optimization, typically there can be no single optimal solution which can simultaneously satisfy all the goals, but rather a set of technologically efficient noninferior or Pareto optimal solutions exists. Generating those Pareto optimal solutions is a challenging task and often difficulties arise in using...

 In the field of reliability optimization often comes the problem of selective maintenance. A system with series and parallel components often have situations where it takes small breaks or intervals and start functioning again. These intervals give the experts time to replace or repair deteriorating components of the system which is termed as selective maintenance. For such system, a decision...