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February 21, 2026International Journal of Services and Operations Management0 citations

Incorporating robust and quasi-robust optimisation methods to model the relief distribution problem under uncertainty

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IIIsraa Ismail

Key Points

  • To develop robust and quasi-robust optimisation methods for relief distribution under uncertain conditions.
  • Adaptation of worst case robust optimisation for supply and demand uncertainties.
  • Development of quasi-robust optimisation for travel time uncertainty.
  • Empirical testing of the model to verify its effectiveness.
  • Successfully minimised deprivation costs associated with relief distribution.
  • Demonstrated improved management of uncertainties in travel time and demand.
  • Increased reliability of delivery times in planned scenarios.

Abstract

This paper addresses the problem of modelling uncertainty in supply, demand, and travel time parameters in relief distribution optimisation models. The model aims to minimise the deprivation cost, expressed as a function of deprivation time, and updates the deprivation status of demand nodes at the beginning of each time period in the planning horizon. The uncertainty realisations in travel time are thus discretised and delays are expressed as number of time periods behind the expected delivery time. The first part of the article adapts the reasonable worst case robust optimisation approach to model uncertainties in supply and demand parameters which are assumed to be uniformly distributed. The second part introduces a novel quasi robust optimisation approach to model uncertainty in travel time where delays in each arc are assumed to be proportional to the assigned arc load for more protection against constraints' violation. The model is tested and verified empirically.

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Cite This Study

Israa Ismail (2026) studied this question.

synapsesocial.com/papers/69994c6f873532290d020daahttps://doi.org/10.1504/ijsom.2026.151745
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