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A multicriteria Master Planning DSS for a sustainable humanitarian supply chain

  • S.I.: Applications of OR in Disaster Relief Operations, Part II
  • Published:
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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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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, University of Toulouse, IMT Mines Albi, Route de Teillet, 81013, Albi Cedex 9, France

    Laura Laguna-Salvadó & Matthieu Lauras

  2. Department of Information, Operations and Management Sciences, Toulouse Business School, 20 Boulevard Lascrosses, 31000, Toulouse, France

    Uche Okongwu

  3. Department of ICT, University of Agder, 4879, Grimstad, Norway

    Tina Comes

  4. Department of Multi-Actor Systems, Delft University of Technology, Delft, The Netherlands

    Tina Comes

Authors
  1. Laura Laguna-Salvadó
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  2. Matthieu Lauras
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  3. Uche Okongwu
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  4. Tina Comes
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Corresponding author

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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