The Maximum Diversity Assortment Selection Problem

  • In this article, we introduce the Maximum Diversity Assortment Selection Problem (MDASP), which is a generalization of the two-dimensional Knapsack Problem (2D-KP). Given a set of rectangles and a rectangular container, the goal of 2D-KP is to determine a subset of rectangles that can be placed in the container without overlapping, i.e., a feasible assortment, such that a maximum area is covered. MDASP is to determine a set of feasible assortments, each of them covering a certain minimum threshold of the container, such that the diversity among them is maximized. Thereby, diversity is defined as the minimum or average normalized Hamming distance of all assortment pairs. MDASP was the topic of the 11th AIMMS-MOPTA Competition in 2019. The methods described in this article and the resulting computational results won the contest. In the following, we give a definition of the problem, introduce a mathematical model and solution approaches, determine upper bounds on the diversity, and conclude with computational experiments conducted on test instances derived from the 2D-KP literature.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Felix PrauseORCiD, Kai Hoppmann-BaumORCiD, Boris DefournyORCiD, Thorsten KochORCiD
Document Type:Article
Parent Title (English):Mathematical Methods of Operations Research
Volume:93
First Page:521
Last Page:554
Publisher:Mathematical Methods of Operations Research
Year of first publication:2021
Preprint:urn:nbn:de:0297-zib-81039
DOI:https://doi.org/https://doi.org/10.1007/s00186-021-00740-2
Accept ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.