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An Approach for Optimal Allocation of Safety Resources: Using the Knapsack Problem to Take Aggregated Cost‐Efficient Preventive Measures

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  • Genserik L. L. Reniers
  • Kenneth Sörensen

Abstract

On the basis of the combination of the well‐known knapsack problem and a widely used risk management technique in organizations (that is, the risk matrix), an approach was developed to carry out a cost‐benefits analysis to efficiently take prevention investment decisions. Using the knapsack problem as a model and combining it with a well‐known technique to solve this problem, bundles of prevention measures are prioritized based on their costs and benefits within a predefined prevention budget. Those bundles showing the highest efficiencies, and within a given budget, are identified from a wide variety of possible alternatives. Hence, the approach allows for an optimal allocation of safety resources, does not require any highly specialized information, and can therefore easily be applied by any organization using the risk matrix as a risk ranking tool.

Suggested Citation

  • Genserik L. L. Reniers & Kenneth Sörensen, 2013. "An Approach for Optimal Allocation of Safety Resources: Using the Knapsack Problem to Take Aggregated Cost‐Efficient Preventive Measures," Risk Analysis, John Wiley & Sons, vol. 33(11), pages 2056-2067, November.
    • Handle: RePEc:wly:riskan:v:33:y:2013:i:11:p:2056-2067
    DOI: 10.1111/risa.12036
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    References listed on IDEAS

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    1. RENIERS, Genserik & SOUDAN, Karel, 2003. "Risicoanalyseprocedures in de scheikundige nijverheid: Resultaten van een semi-kwalitatief onderzoek bij 24 chemische plants," Economic and Social Journal (Economisch en Sociaal Tijdschrift), University of Antwerp, Faculty of Business and Economics, vol. 57(3), pages 249-274, December.
    2. Eric D. Smith & William T. Siefert & David Drain, 2009. "Risk matrix input data biases," Systems Engineering, John Wiley & Sons, vol. 12(4), pages 344-360, December.
    3. Martello, Silvano & Pisinger, David & Toth, Paolo, 2000. "New trends in exact algorithms for the 0-1 knapsack problem," European Journal of Operational Research, Elsevier, vol. 123(2), pages 325-332, June.
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