Warehouses are key elements of supply chain networks, and great attention is paid to increase theirefficiency. Highly volatile space requirements are enablers of innovative resource sharing concepts,where warehouse capacities are traded on online platforms. In this context, our paper introduces theon-demand warehousing problem from the perspective of platform providers. The objective priori-tises demand–supply matching with maximisation of the number of transactions. If there is a tie, thesecondary objective maximises the number of suppliers matched with at least one customer and thenumber of customers that have matches within a specific threshold with respect to the minimumachievable cost. Besides the mathematical integer programming formulation, a myopic list-basedheuristic and an efficient matheuristic approach are presented and benchmarked against the per-formance of a commercial optimisation solver. The impact of several parameters on the platform’sobjective is analysed. A particularly relevant finding is that the pricing flexibility on the demand sidedoes not necessarily imply higher payments to the supply side. All data instances are made availablepublicly to encourage more researchers to work on this timely and challenging topic.

The on-demand warehousing problem

Simona Mancini;
2022-01-01

Abstract

Warehouses are key elements of supply chain networks, and great attention is paid to increase theirefficiency. Highly volatile space requirements are enablers of innovative resource sharing concepts,where warehouse capacities are traded on online platforms. In this context, our paper introduces theon-demand warehousing problem from the perspective of platform providers. The objective priori-tises demand–supply matching with maximisation of the number of transactions. If there is a tie, thesecondary objective maximises the number of suppliers matched with at least one customer and thenumber of customers that have matches within a specific threshold with respect to the minimumachievable cost. Besides the mathematical integer programming formulation, a myopic list-basedheuristic and an efficient matheuristic approach are presented and benchmarked against the per-formance of a commercial optimisation solver. The impact of several parameters on the platform’sobjective is analysed. A particularly relevant finding is that the pricing flexibility on the demand sidedoes not necessarily imply higher payments to the supply side. All data instances are made availablepublicly to encourage more researchers to work on this timely and challenging topic.
2022
combinatorial optimisation; demand–supply matching; matheuristic; Sharing economy; warehouse
File in questo prodotto:
File Dimensione Formato  
2022-on_demand_warehousing_IJPR.pdf

accesso aperto

Tipologia: versione editoriale
Dimensione 2.78 MB
Formato Adobe PDF
2.78 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/348819
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 7
social impact