### Abstract

Language | English |
---|---|

Number of pages | 32 |

Journal | Annals of Operations Research |

DOIs | |

Publication status | E-pub ahead of print - 17 May 2018 |

### Fingerprint

### Cite this

}

**Sustainable distribution system design : a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routing model.** / Validi, Sahar; Bhattacharya, Arijit ; Byrne , P. J.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Sustainable distribution system design

T2 - Annals of Operations Research

AU - Validi, Sahar

AU - Bhattacharya, Arijit

AU - Byrne , P. J.

PY - 2018/5/17

Y1 - 2018/5/17

N2 - This article introduces a sustainable integrated bi-objective location-routing model, its two-phase solution approach and an analysis procedure for the distribution side of three-echelon logistics networks. The mixed-integer programming model captures several real-world factors by introducing an additional objective function and a set of new constraints in the model that outbound logistics channels find difficult to reconcile. The sustainable model minimises CO2 emissions from transportation and total costs incurred in facilities and the transportation channels. Design of Experiment (DoE) is integrated to the meta-heuristic based optimiser to solve the model in two phases. The DoE-guided solution approach enables the optimiser to offer the best stable solution space by taking out solutions with poor design features from the space and refining the feasible solutions using a convergence algorithm thereby selecting the realistic results. Several alternative solution scenarios are obtained by prioritising and ranking the realistic solution sets through a multi-attribute decision analysis tool, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The robust model provides the decision maker the ability to take decisions on sustainable open alternative optimal routes. The outcomes of this research provide theoretical and methodological contributions, in terms of integrated bi-objective location-routing model and its two-phase DoE-guided meta-heuristic solution approach, for the distribution side of three-echelon logistics networks.

AB - This article introduces a sustainable integrated bi-objective location-routing model, its two-phase solution approach and an analysis procedure for the distribution side of three-echelon logistics networks. The mixed-integer programming model captures several real-world factors by introducing an additional objective function and a set of new constraints in the model that outbound logistics channels find difficult to reconcile. The sustainable model minimises CO2 emissions from transportation and total costs incurred in facilities and the transportation channels. Design of Experiment (DoE) is integrated to the meta-heuristic based optimiser to solve the model in two phases. The DoE-guided solution approach enables the optimiser to offer the best stable solution space by taking out solutions with poor design features from the space and refining the feasible solutions using a convergence algorithm thereby selecting the realistic results. Several alternative solution scenarios are obtained by prioritising and ranking the realistic solution sets through a multi-attribute decision analysis tool, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The robust model provides the decision maker the ability to take decisions on sustainable open alternative optimal routes. The outcomes of this research provide theoretical and methodological contributions, in terms of integrated bi-objective location-routing model and its two-phase DoE-guided meta-heuristic solution approach, for the distribution side of three-echelon logistics networks.

KW - Sustainable logistics network

KW - Location-routing

KW - Bi-objective programming

KW - Mixed-integer programming

KW - Multi-attribute decision analysis

KW - DoE-guided meta-heuristic solution

UR - http://www.scopus.com/inward/record.url?scp=85047162112&partnerID=8YFLogxK

U2 - 10.1007/s10479-018-2887-y

DO - 10.1007/s10479-018-2887-y

M3 - Article

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

ER -