A multicriteria Master Planning DSS for a sustainable humanitarian supply chain

Abstract

Humanitarian supply chains (HSCs) contribute significantly to achieving effective and rapid responses to natural and man-made disasters. Though humanitarian organizations have during the last decades made considerable efforts to improve the response to crises in terms of effectiveness and efficiency, HSCs are still faced with so many challenges, one of which is the incorporation of sustainability dimensions (economic, social and environmental) in the management of their supply chains. In the literature, some authors have highlighted that the planning and achievement of sustainability performance objectives in humanitarian operations is hindered by the lack of decision support systems (DSS). Therefore, this paper proposes a multi-objective Master Planning DSS for managing sustainable HSCs. This Master Planning DSS includes: (1) the definition of a set of metrics for measuring the performance of a sustainable HSC; (2) an algorithm to solve the multi-objective problem; and (3) a Master Planning mathematical model to support the tactical planning of the sustainable HSC. Using the information gathered from field research and the literature, an illustrative numerical example is presented to demonstrate the implementation and utility of the proposed DSS. The results show that the order in which the three sustainability dimensions (economic, social and environmental) are prioritized has some impact on the performance measures. Therefore, it is important to fix a tolerance that would enable to obtain an acceptable balance (trade-off) between the three sustainability objectives, in line with the prioritization choice of the decision maker.

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Correspondence to Uche Okongwu.

Appendices

Appendix 1: Network flow database

Supplier code Supplier location Supplier Item Factory price par unit (CHF) Supply capacity/week
(a) Supplier data
1001 International Relief supplier A Blanket light thermal 6 12,000
1002 International Relief supplier B Blanket light thermal 5 13,750
1003 International Relief supplier C Blanket light thermal 7 9900
1006 International Relief supplier D Family tent 150 2000
1009 International Relief supplier E Family tent 160 2000
1009 International Relief supplier E Blanket light thermal 6 1200
1010 International Relief supplier F Family tent 170 3000
1011 International Relief supplier G Blanket light thermal 6 5000
1012 Regional Panama supplier Blanket light thermal 8 6000
1012 Regional Panama supplier Family tent 300 1000
1013 Local Nicaragua supplier Family tent 250 500
1014 Local Colombia supplier Family tent 250 500
1014 Local Colombia supplier Blanket light thermal 7 5000
1015 Local Honduras supplier Blanket light thermal 7 5000
1016 Local Guatemala supplier Blanket light thermal 7 5000
1017 Local Dom. Rep. supplier Blanket light thermal 7 5000
1018 Local Costa Rica supplier Blanket light thermal 7 5000
1013 Local Nicaragua supplier Blanket light thermal 7 5000
Serial number Warehouse code National society Blanket contingency stock Family tent contingency stock
(b) Inventory input data of the RLU and LUs
1 2001 Panama RLU 40,000 10,000
2 2002 Colombia LU 20,000 5000
3 2003 Nicaragua LU 8000 2000
4 2004 Honduras LU 20,000 5000
5 2005 FR Guadeloupe LU 20,000 5000
6 2006 Guatemala LU 8000 2000
7 2007 Dominican Rep. LU 8000 2000
8 2008 Costa Rica LU 8000 2000
cid Demand point Item cpen cqua
Wk 1 Wk 2 Wk 3 Wk 4 Wk 5 Wk 6 Wk 7
(c) Demand input data
3001 Dominican Rep. Blanket 1.5 2000 0 0 0 2000 0 0
3001 Dominican Rep. Family tent 1.5 500 0 0 0 500 1000 0
3002 Nicaragua North Blanket 1.5 0 5000 0 3000 0 500 0
3002 Nicaragua North Family tent 1.5 0 1000 0 700 0 5000 0
3003 Nicaragua South Blanket 1.5 9000 0 0 0 0 1000 0
3003 Nicaragua South Family tent 1.5 2000 0 0 0 0 0 0
3004 Honduras Blanket 1.5 0 6000 0 0 0 0 5000
3004 Honduras Family tent 1.5 0 1500 0 0 0 0 1000
3005 Colombia Blanket 1.25 7500 0 0 0 5000 0 0
3005 Colombia Family tent 1.25 1500 0 0 0 1000 0 0
3006 Guatemala Blanket 1.25 0 0 9000 0 0 0 9000
3006 Guatemala Family tent 1.25 0 0 3000 0 0 0 3000
3007 Haiti Blanket 1.5 20,000 10,000 0 0 0 0 0
3007 Haiti Family tent 1.5 5000 5000 0 0 0 0 0
3008 Haiti NGO Blanket 1.1 0 2000 0 0 0 2500 0
3008 Haiti NGO Family tent 1.1 0 500 0 0 0 600 0
Serial number Origin Destination Mode Lead time Product CO2/unit Cost/unit Social fexp
fori fdes ftlt fenv fcost fsoc Wk 1 Wk 2
(d) Input data of flows
1 1001 2001 Sea 2 Blanket 0.0182 5.011 0 0 0
2 2001 2002 Air 1 Blanket 0.0622 0.094 0 0 0
3 2001 2003 Air 1 Blanket 0.0697 0.106 0 0 0
4 2001 2004 Air 1 Blanket 0.0871 0.132 0 0 0
5 2001 2005 Air 1 Blanket 0.1763 0.267 0 0 0
6 2001 2006 Air 1 Blanket 0.1146 0.174 0 0 0
7 2001 2007 Air 1 Blanket 0.1250 0.189 0 0 0
8 2001 2008 Air 1 Blanket 0.0414 0.063 0 0 0
9 2001 2002 Multi 2 Blanket 0.0058 0.067 0 0 0
10 2001 2005 Sea 2 Blanket 0.0007 0.005 0 0 0
11 2001 2007 Sea 2 Blanket 0.0007 0.005 0 0 0
12 2001 2003 Road 1 Blanket 0.0058 0.071 0 0 0
13 2001 2004 Road 1 Blanket 0.0086 0.105 0 0 0
14 2001 2006 Road 1 Blanket 0.0111 0.136 0 0 0
15 2001 2008 Road 1 Blanket 0.0045 0.056 0 0 0

Appendix 2: Experimental plan lexicographic orders

Order LO0 LO1 LO2 LO3
A (example) Effectiveness Economic Social Environmental
B Effectiveness Economic Environmental Social
C Effectiveness Social Economic Environmental
D Effectiveness Social Environmental Economic
E Effectiveness Environmental Economic Social
F Effectiveness Environmental Social Economic

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Laguna-Salvadó, L., Lauras, M., Okongwu, U. et al. A multicriteria Master Planning DSS for a sustainable humanitarian supply chain. Ann Oper Res 283, 1303–1343 (2019). https://doi.org/10.1007/s10479-018-2882-3

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Keywords

  • Disaster relief operations
  • Humanitarian supply chain
  • Sustainable supply chain
  • Sustainability
  • Master Planning
  • Multi-objective decision support system