Routing and resource allocation in non-profit settings with equity and efficiency measures under demand uncertainty

Faisal Alkaabneh, Karmel S. Shehadeh, Ali Diabat

Research output: Contribution to journalArticlepeer-review


Motivated by food distribution operations for non-profit organizations, we study a variant of the stochastic routing-allocation problem under demand uncertainty, in which one decides the assignment of trucks for demand nodes, the sequence of demand nodes to visit (i.e., truck route), and the allocation of food supply to each demand node. We propose three stochastic mixed-integer programming (SMIP) models representing different performance measures important to food banks, namely maximizing efficiency, maximizing equity, and maximizing efficiency and equity simultaneously. To solve practical large-scale instances, we develop an original matheuristic based on adaptive large-scale neighborhood search. Using real-world data based on real-life instances, we conduct an extensive numerical experiment to assess the computational performance of our approach and derive insights relevant to food banks. The proposed matheuristic produces high-quality solutions quickly with an optimality gap never exceeding 4.11% on tested instances. We also demonstrate the performance of the three models in terms of service levels, food waste, and equity.

Original languageEnglish (US)
Article number104023
JournalTransportation Research Part C: Emerging Technologies
StatePublished - Apr 2023


  • Food banks
  • Humanitarian logistics
  • Matheuristic
  • Resource allocation
  • Vehicle routing

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Management Science and Operations Research


Dive into the research topics of 'Routing and resource allocation in non-profit settings with equity and efficiency measures under demand uncertainty'. Together they form a unique fingerprint.

Cite this