Abstract Consider two principles for social evaluation. The first, “laissez-faire”, says that mean-preserving redistribution away from laissez-faire incomes should be regarded as a worsening. This principle captures key aspect of libertarian political philosophy. second, weak Pareto, states an increase in the disposable income each individual improvement. We show combination implies total ought...

In this paper, we propose to integrate particle swarm optimization algorithm into cultural algorithms frame to develop a more efficient cultural particle swarm algorithms (CPSA) for constrained multi-objective optimization problem. In our CPSA, the population space of cultural algorithms consists of n+1 subswarms which are used to search for the n single-objective optimums and an additional mul...

Multi-objective optimisation problems normally have not one but a set of solutions, which are called Pareto-optimal solutions or non-dominated solutions. Once a Pareto-optimal set has been obtained, the decision-maker faces the challenge of analysing a potentially large set of solutions. Selecting one solution over others can be quite a challenging task because the Pareto set can contain an unm...

The Pareto set of a multiobjective optimization problem consists of the solutions for which one or more objectives can not be improved without deteriorating one or more other objectives. We consider problems with linear objectives and linear constraints and use Adjustable Robust Optimization and Polynomial Optimization as tools to approximate the Pareto set with polynomials of arbitrarily large...

In this paper we examine the usefulness of the M/Pareto process as a model for broadband traffic. We show that the queueing performance of the M/Pareto process depends upon the level of aggregation in the process. When the level of aggregation is high, the M/Pareto converges to a long range dependent Gaussian process. For lower levels of aggregation, the M/Pareto is capable of modeling the queu...

In this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. Two objective functions, real power loss and energy not supplied index (ENS), were utilized. Multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how P...

In the present study, we propose a new family of distributions namely Pareto-X family. A sub model proposed called Pareto-Weibull (PW) distribution is discussed. The maximum likelihood estimators parameters are obtained. Different distributional properties described. order to assess applicability model, two real-life applications from environmental and biological study considered. practical sho...

Understanding Pareto Inefficient Intrahousehold Allocations Udry (1996) uses household survey data and finds that the allocation of resources within households is Pareto inefficient, contradicting the main assumption of most collective models of intrahousehold bargaining. He finds that among plots planted with the same crop in the same year, within a given household, those controlled by women p...

Most of the engineering problems are modeled as evolutionary multiobjective optimization problems, but they always ask for only one best solution, not a set of Pareto optimal solutions. The decision maker’s subjective information plays an important role in choosing the best solution from several Pareto optimal solutions. Generally, the decision-making processing is implemented after Pareto opti...