The Pareto stability is one of solution concepts in two-sided matching markets with ties. It is known that there always exists a Pareto stable matching in the many-to-many setting. In this paper, we consider the following generalization of the Pareto stable matching problem in the many-to-many setting. Each agent v of one side has a matroid defined on the set of edges incident to v, and the set...

The phrase \optimal program specialization" was de ned by Jones et al. in 1993 to capture the idea of a specializer being strong enough to remove entire layers of interpretation. As it has become clear that it does not imply \optimality" in the everyday meaning of the word, we propose to rename the concept \Jones-optimality". We argue that the 1993 de nition of Jones-optimality is in principle ...

and Applied Analysis 3 x0, y0 ∈ L StrD F, S resp., x0, y0 ∈ LW MinD F, S , if there exists a neighborhood U of x0 in X such that y0 ∈ StrD F U ∩ S ( resp., y0 ∈ W minD F U ∩ S ) , that is, ∀x ∈ S∩U, F x − y0 ∩ −D\{0} ∅ resp. ∀x ∈ S∩U, F x − y0 ∩ − intD ∅. 2.4 We will say that x0, y0 is a global strict global weak minimizers when U X. The set of all global strict minimizers resp., weak minimizer...

In his paper "Extended Sympathy and the Possibility of Social Choice", Professor Arrow first considers an approach to individual utilities which is "strictly ordinal" and rules out interpersonal comparisons. This is the approach he took when he formulated his original impossibility theorem [1]. He then takes up an approach which allows interperso~al comparisons, but only of an ordinal kind. The...

A fundamental resource allocation setting is the random assignment problem in which agents express preferences over objects that are then randomly allocated to the agents. In 2001, Bogomolnaia and Moulin presented the probabilistic serial (PS) mechanism that is an anonymous, neutral, Pareto optimal, and weak strategyproof mechanism when the preferences are considered with respect to stochastic ...

Many real-world optimization problems have several, usually conflicting objectives. Evolutionary multi-objective optimization usually solves this predicament by searching for the whole Pareto-optimal front of solutions, and relies on a decision maker to finally select a single solution. However, in particular if the number of objectives is large, the number of Pareto-optimal solutions may be hu...

Although a number of multiobjective evolutionary algorithms have been proposed over the last two decades, not much effort has been made to deal with variable linkages in multiobjective optimization. Recently, we have suggested a general framework of multiobjective evolutionary algorithms based on decomposition (MOEA/D) [1]. MOEA/D decomposes a MOP into a number of scalar optimization subproblem...

For decision support under a multiobjective environment, it is effective to offer a Pareto optimal solution set with uniform distribution to the decision-maker. In this paper, a new optimization method for obtaining a Pareto optimal solution set with such uniform distribution is proposed. In order to overcome the difficulty of realizing this goal, the concept of cannibalism is introduced in BUG...

In this paper, the average cases of Markov decision processes with uncertainty is considered. That is, a controlled Markov set-chain model with a finite state and action space is developed by an interval arithmetic analysis, and we will find a Pareto optimal policy which maximizes the average expected rewards over all stationary policies under a new partial order. The Pareto optimal policies is...