Table 1 Summary of the research... | Emerald Publishing

Table 1

Summary of the research contribution to the existing literature related to the DRCLAR design problem

Authors	Title	Model objective	Tool/Methods	Major findings
Ukkusuri and Yushimito (2008)	“Location routing approach for the humanitarian prepositioning problem”	Minimizing the fixed costs and the routing costs and maximizing the probability of the inventory to reach all the demand points	A combination of the most reliable path and integer programming model	The proposed method can reduce the problem complexity and solve the problem efficiently
Lin et al. (2011)	“A logistic model for emergency supply of critical items in the aftermath of a disaster”	Minimizing the total unsatisfied demand, the total travel time and the difference in the satisfaction between the demand nodes	A genetic algorithm based-heuristic and decomposition and assignment heuristic	The proposed model performs well in the disaster relief operation, where prioritizing delivery is important for the emergency supply of critical items
Rath and Gutjahr (2014)	“A math-heuristic for the warehouse location-routing problem in disaster relief”	Minimizing the total fixed costs and operative costs and maximizing the covered demand	Mixed-integer linear programming and math heuristic technique based on the adaptive ε-constraint algorithm	The results of the math heuristic technique are compared to those obtained from an application of the NSGA-II metaheuristic
Zhang et al. (2018)	“Sustainable multi-depot emergency facilities location-routing problem with uncertain information”	Minimizing travel time, emergency travel relief costs and carbon dioxide emissions	A hybrid intelligent algorithm that integrates simulation and a genetic algorithm	Illustrating the optimization ideas and robustness and effectiveness of the proposed algorithm
Liu et al. (2019)	“Location-routing problem for relief distribution in the early post-earthquake stage from the perspective of fairness”	Minimizing the maximum loss of demand node, the total loss of demand node and the maximum time required for the demand node to receive relief	Lexicographic order object optimization method with a hybrid heuristic algorithm	A proposed hybrid heuristic algorithm not only quickly solve the problem but also take fairness and utility into consideration
Alinaghian et al. (2019)	“A mathematical model for location of temporary relief centers and dynamic routing of aerial rescue vehicles”	Minimizing the arrival time at the last designated temporary relief center	A hybrid metaheuristic algorithm based on scatter search combined with variable neighborhood search	The proposed algorithm performs well after being compared with an exact method, scatter search and genetic algorithm
Ghasemi et al. (2019)	“Uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning”	Minimizing the amount of shortage of relief supplies and the total costs consisting of the cost of establishing relief facilities and the cost of human casualties	Modified multiple-objective particle swarm optimization, non-dominated sorting genetic algorithm-II and ε-constraint method	The three combined methods successfully solve the model. The sensitivity analysis shows that the increase in the number of affected people will lead to an increase in the accommodation centers
Khorsi et al. (2020)	“A multi-objective multi-period for humanitarian relief logistics with split delivery and multiple uses of vehicles”	Minimizing the total amount of unsatisfied demand, the total travel time, the sum of the absolute deviations of a fraction of unsatisfied demands	An augmented ε-constraint method (AUGMECON)	The Pareto solutions generated by AUGMECON suggest that the simultaneous consideration of three objectives will improve the effectiveness of distribution efforts
Current paper	“Cross-evaluation based-super efficiency DEA approach to designing disaster recovery center location-allocation-routing network schemes”	Minimizing the total cost, total routing distance and the longest delivery distance. Maximizing the expected demand covered	Goal programming and cross-evaluation based-super-efficiency data envelopment analysis	The proposed approach helps decision-makers design efficient disaster recovery center location-allocation-routing network schemes

Authors	Title	Model objective	Tool/Methods	Major findings
Ukkusuri and Yushimito (2008)	“Location routing approach for the humanitarian prepositioning problem”	Minimizing the fixed costs and the routing costs and maximizing the probability of the inventory to reach all the demand points	A combination of the most reliable path and integer programming model	The proposed method can reduce the problem complexity and solve the problem efficiently
Lin et al. (2011)	“A logistic model for emergency supply of critical items in the aftermath of a disaster”	Minimizing the total unsatisfied demand, the total travel time and the difference in the satisfaction between the demand nodes	A genetic algorithm based-heuristic and decomposition and assignment heuristic	The proposed model performs well in the disaster relief operation, where prioritizing delivery is important for the emergency supply of critical items
Rath and Gutjahr (2014)	“A math-heuristic for the warehouse location-routing problem in disaster relief”	Minimizing the total fixed costs and operative costs and maximizing the covered demand	Mixed-integer linear programming and math heuristic technique based on the adaptive ε-constraint algorithm	The results of the math heuristic technique are compared to those obtained from an application of the NSGA-II metaheuristic
Zhang et al. (2018)	“Sustainable multi-depot emergency facilities location-routing problem with uncertain information”	Minimizing travel time, emergency travel relief costs and carbon dioxide emissions	A hybrid intelligent algorithm that integrates simulation and a genetic algorithm	Illustrating the optimization ideas and robustness and effectiveness of the proposed algorithm
Liu et al. (2019)	“Location-routing problem for relief distribution in the early post-earthquake stage from the perspective of fairness”	Minimizing the maximum loss of demand node, the total loss of demand node and the maximum time required for the demand node to receive relief	Lexicographic order object optimization method with a hybrid heuristic algorithm	A proposed hybrid heuristic algorithm not only quickly solve the problem but also take fairness and utility into consideration
Alinaghian et al. (2019)	“A mathematical model for location of temporary relief centers and dynamic routing of aerial rescue vehicles”	Minimizing the arrival time at the last designated temporary relief center	A hybrid metaheuristic algorithm based on scatter search combined with variable neighborhood search	The proposed algorithm performs well after being compared with an exact method, scatter search and genetic algorithm
Ghasemi et al. (2019)	“Uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning”	Minimizing the amount of shortage of relief supplies and the total costs consisting of the cost of establishing relief facilities and the cost of human casualties	Modified multiple-objective particle swarm optimization, non-dominated sorting genetic algorithm-II and ε-constraint method	The three combined methods successfully solve the model. The sensitivity analysis shows that the increase in the number of affected people will lead to an increase in the accommodation centers
Khorsi et al. (2020)	“A multi-objective multi-period for humanitarian relief logistics with split delivery and multiple uses of vehicles”	Minimizing the total amount of unsatisfied demand, the total travel time, the sum of the absolute deviations of a fraction of unsatisfied demands	An augmented ε-constraint method (AUGMECON)	The Pareto solutions generated by AUGMECON suggest that the simultaneous consideration of three objectives will improve the effectiveness of distribution efforts
Current paper	“Cross-evaluation based-super efficiency DEA approach to designing disaster recovery center location-allocation-routing network schemes”	Minimizing the total cost, total routing distance and the longest delivery distance. Maximizing the expected demand covered	Goal programming and cross-evaluation based-super-efficiency data envelopment analysis	The proposed approach helps decision-makers design efficient disaster recovery center location-allocation-routing network schemes