MAO group - Models and Algorithms for Optimization

Dept. of Information Engineering                                                                      University of Brescia





Contacts

Dip. di Ingegneria dell'Informazione
Universita' degli Studi di Brescia
via Branze, 38
25123, Brescia
Italy

Telephone:
+39 030 371 5448
+39 030 371 5935
+39 030 371 5757


Since 2007, MAO is the Operational Reserch group working at the Department of Information Engineering of the University of Brescia, Italy. It is part of the inter-departmental group OR@BRESCIA (University of Brescia, Italy).

Here you can find all the material (benchmark instances, results) available and freely downloadable regarding the following publications:


Unpublished

  • Bonomi V., Mansini R., Zanotti R. (under review). Mediating governance goals with patients and nurses satisfaction: a multi-actor multi-objective problem including fairness.     >> Material


    • 2023

  • Gobbi A., Manerba D., Mansini R., Zanotti R. (2023). Hybridizing adaptive large neighborhood search with kernel search: a new solution approach for the nurse routing problem with incompatible services and minimum demand. International Transactions in Operational Research 30.1 (2023): 8-38. >> Material


  • Mansini R., Zanella M., Zanotti R. (2023). Optimizing a complex multi-objective personnel scheduling problem jointly complying with requests from customers and staff. Omega 114 (2023): 102722     >> Material


    • 2022

  • Lamanna L., Mansini R., Zanotti R. (2022). A Two-phase Kernel Search variant for the Multidimensional Multiple-choice Knapsack Problem. 297 (1), pp. 53-65. >> Material


    • 2020

  • Mansini R., Zanotti R. (2020). A Core-Based Exact Algorithm for the Multidimensional Multiple-Choice Knapsack Problem. INFORMS Journal on Computing 32 (4), pp. 1061-1079.     >> Material

  • Hanafi S., Mansini R., Zanotti R. (2020). Multi Visit Team Orienteering Problem with Precedence Constraints. European Journal of Operational Research 282 (2), pp. 515-529.     >> Material


    • 2017

  • Beraldi P., Bruni M.E., Manerba D., Mansini R (2017). A Stochastic Programming approach for the Traveling Purchaser Problem. IMA Journal of Management Mathematics 28(1), pp 41-63.     >> Material

  • Colombi M., Mansini R., Savelsbergh M. (2017). The generalized independent set problem: Polyhedral analysis and solution approaches. European Journal of Operational Research 260(1) pp 41-55.     >> Material


    • 2016

  • Gendreau M., Manerba D., Mansini R. (2015). The Multi-vehicle Traveling Purchaser Problem with Pairwise Incompatibility Constraints and Unitary Demands: A Branch-and-Price approach. European Journal of Operational Research 248(1), 59-71.     >> Material


    • 2015

  • Manerba D., Mansini R. (2016). A branch-and-cut algorithm for the Multi-vehicle Traveling Purchaser Problem with Pairwise Incompatibility Constraints. Networks 65(2), 139-154.     >> Material


    • 2014

  • Colombi M., Mansini R. (2014). New results for the Directed Profitable Rural Postman Problem. European Journal of Operational Research 238(3), pp. 760-773.     >> Material

  • Manerba D., Mansini R. (2014). An Effective Matheuristic for the Capacitated Total Quantity Discount Problem. Computers & Operations Research 41(1), pp. 1-11.     >> Material


    • 2012

  • Manerba D., Mansini R. (2012). An Exact Algorithm for the Capacitated Total Quantity Discount Problem. European Journal of Operational Research 222(2) pp. 287-300.     >> Material


    • 2010

  • Angelelli E., R. Mansini, M.G. Speranza (2010). Kernel search: A general heuristic for the multi-dimensional knapsack problem. Computers & Operations Research 37, pp. 2017-2026.     >> Material