In real-world applications of optimization, optimal solutions are often of limited value, because disturbances of or changes to input data may diminish the quality of an optimal solution or even render it infeasible. One way to deal with uncertain input data is robust optimization, the aim of...

In this paper we present new concepts of efficiency for uncertain multi-objective optimization problems. We analyze the connection between the concept of minmax robust efficiency presented by Ehrgott et al. (Eur J Oper Res, <CitationRef CitationID="CR14">2014</CitationRef>, doi:<ExternalRef> <RefSource>10.1016/j.ejor.2014.03.013</RefSource> <RefTarget Address="10.1016/j.ejor.2014.03.013" TargetType="DOI"/> </ExternalRef>) and the upper set less order...</refsource></externalref></citationref>

This paper finds a high correlation between the open to close returns for U.S. stocks in the previous trading day and the Japanese equity market performance in the current period. In contrast, the Japanese market has only a small impact on the U.S. return in the current period. High correlations...

We examine the issue of optimal asset allocation among three broad classes of assetsÃÃLarge Stocks (proxied by the S&P composite index); real estate assets (a portfolio of thirty Equity Real Estate Investment Trusts (REITs) traded on major stock exchanges); and the risk-free asset (the...

Minmax regret optimization aims at finding robust solutions that perform best in the worst-case, compared to the respective optimum objective value in each scenario. Even for simple uncertainty sets like boxes, most polynomially solvable optimization problems have strongly NP-complete minmax...

We consider the problem of evacuating an urban area. Several planning aspects need to be considered in such a scenario, which are usually considered separately. We propose a macroscopic multi-criteria optimization model that includes several such questions simultaneously, and develop a genetic...

In this paper we consider nonlinear integer optimization problems. Nonlinear integer programming has mainly been studied for special classes, such as convex and concave objective functions and polyhedral constraints. In this paper we follow an other approach which is not based on convexity or...

This paper presents a new concept of partial coverage distance, where demand points within a given threshold distance of a new facility are covered in the traditional sense, while non-covered demand points are penalized an amount proportional to their distance to the covered region. Two single...

We introduce the path player game, a noncooperative network game with a continuum of mutually dependent set of strategies. This game models network flows from the point of view of competing network operators. The players are represented by paths in the network. They have to decide how much flow...

We present a game-theoretic model for the line planning problem in public transportation, in which each line acts as player. Each player aims to minimize its own delay, which is dependent on the traffic load along its edges. We show that there exists a line plan at equilibrium, which minimizes...