In multi-objective mixed-integer convex optimization, multiple convex objective functions need to be optimized simultaneously while some of the variables are restricted to take integer values. In this paper, we present a new algorithm to compute an enclosure of the nondominated set of such...

This paper describes theNeighbourhood Search, an effectivemethod that we suggest for constructing Pareto sets in multiple objective problems with conegenerated orders. TheNeighbourhood Search is then applied to discounted Markov Decision Processes, resulting in original statements about...

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>

While branch and bound based algorithms are a standard approach to solve single-objective (mixed-)integer optimization problems, multi-objective branch and bound methods are only rarely applied compared to the predominant objective space methods. In this paper we propose modifications to...

In this paper, we present an outer approximation algorithm for computing the Edgeworth–Pareto hull of multi-objective mixed-integer linear programming problems (MOMILPs). It produces the extreme points (i.e., the vertices) as well as the facets of the Edgeworth–Pareto hull. We note that...

In multi-objective mixed-integer convex optimization, multiple convex objective functions need to be optimized simultaneously while some of the variables are restricted to take integer values. In this paper, we present a new algorithm to compute an enclosure of the nondominated set of such...