How should we allocate a social endowment of objects among a group of agents when monetary compensation is not possible? Typical examples are the assignment of offices among faculty and the assignment of tasks among subalterns. We follow an axiomatic approach and impose two properties on rules: Pareto-efficiency and consistency. Previous research arrived at a “dictatorship” result imposing anot...

Pareto front optimization has been commonly used for balancing trade-offs between different estimated responses. Using maximum likelihood or least squares point estimates or the worst case confidence bound values of the response surface, it is straightforward to find preferred locations in the input factor space that simultaneously perform well for the various responses. A new approach is propo...

In this study, a hybrid approach combining trust region (TR) algorithm and particle swarm optimization (PSO) is proposed to solve multi-objective optimization problems (MOOPs). The proposed approach integrates the merits of both TR and PSO. Firstly, the MOOP converting by weighted method to a single objective optimization problem (SOOP) and some of the points in the search space are generated. ...

Given a first set of observations from a design of experiments sampled randomly in the design space, the corresponding set of non-dominated points usually does not give a good approximation of the Pareto front. We propose here to study this problem from the point of view of multivariate analysis, introducing a probabilistic framework with the use of copulas. This approach enables the expression...

Real life problems involve seldom only one criterion, but multiple criteria should be optimised at the same time. The criteria can even be conflicting each other, so the classical techniques used in single criteria optimization cannot be simply reused. Many ideas have been presented in the literature for addressing multiple criteria optimization problems; one of the ideas is to provide the so-c...

Minimum Spanning Tree (MST) problem is of high importance in network optimization. The multi-criteria MST (mc-MST) is a more realistic representation of the practical problem in the real-world, but it is diicult for the traditional network optimization technique to deal with. In this paper, a genetic algorithm (GA) approach is developed to deal with this problem. Without neglecting its network ...

Multidisciplinary Design Optimization (MDO) problems can have a unique objective or be multi-objective. In this paper, we are interested in MDO problems having at least two conflicting objectives. This characteristic ensures the existence of a set of compromise solutions called Pareto front. We treat those MDO problems like Multi-Objective Optimization (MOO) problems. Actual MOO methods suffer ...

The conversion and extension of the Incremental Pareto-Coevolution Archive algorithm (IPCA) into the domain of Genetic Programming classification is presented. In particular, the coevolutionary aspect of the IPCA algorithm is utilized to simultaneously evolve a subset of the training data that provides distinctions between candidate classifiers. Empirical results indicate that such a scheme sig...

In a series of articles and a book, Louis Kaplow and Steven Shavell (KS) articulated and defended the normative approach of standard law-and-economics. KS also argued that legal analysts should think in welfare-economic terms exclusively when advising on normative social issues of tremendous import. This thesis generated controversy within the legal academic community because it implied that nu...

The planning phase of every construction project is entangled with multiple and occasionally conflicting criteria which need to be optimized simultaneously. Multi-criterion decision-making (MCDM) approaches can aid decision-makers in selecting the most appropriate solution among numerous potential Pareto optimal solutions. An evidential reasoning (ER) approach was applied for the first time in ...