In this paper, we propose and operationalize a new method for optimizing shelf arrangements. We show that there are important dependencies between the layout of the shelf and stock-keeping unit (SKU) sales and marketing effectiveness. The importance of these dependencies is further shown by the...

This paper presents and compares three heuristics for the combinatorial auctionproblem. Besides a simple greedy (SG) mechanism, two metaheuristics, a simulatedannealing (SA), and a genetic algorithm (GA) approach are developedwhich use the combinatorial auction process to an allocation with...

Der Beitrag stellt ein Simulated Annealing-Verfahren zur Lösung des um Zeitfensterrestriktionen erweiterten Standardproblems vor. Die Zielfunktion berücksichtigt zwei Zielkriterien, die Minimierung der Fahrzeuganzahl als primäres und die Minimierung der Gesamtentfernung als sekundäres...

We develop a hybrid algorithm using Genetic Algorithms (GA) and Simulated Annealing (SA) to solve multi-objective step function maximization problems. We then apply the algorithm to a specific economic problem which is taken out of the corporate governance literature.

In simulation studies Latent Factor Prediction Pursuit outperformed classical reduced rank regression methods. The algorithm described so far for Latent Factor Prediction Pursuit had two shortcomings: It was only implemented for situations where the explanatory variables were of full colum rank....

This paper addresses the robust spanning tree problem with interval data, i.e. the case of classical minimum spanning tree problem when edge weights are not fixed but take their values from some intervals associated with edges. The problem consists in finding a spanning tree that minimizes...

This paper addresses the robust shortest path problem with interval data, i.e. the case of classical shortest path problem with given source and sink when arc weights are not fixed but take their values from some intervals associated with arcs. The problem consists in finding a shortest path...