Review study of the optimization model for humanitarian logistic in disaster management
| Authors | Objective function | Otherobjective | Fs | E | RT | D/S | Multi /singleobjective | Constraint | Mathmodel | Exactapproach | Solution algorithm | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cost | Time | Evacuation ofdistance | Capacity | Budget | Limitsite | Transportationmode | Items | Demand | ||||||||||
| (Caglayan and Satoglu, 2021) | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | MILP | CPLEX | Augmencon epsilon-constraint | |||||||
| (Jamali et al., 2021) | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | ✓ | MILP | GAMS | GP | ||||
| (Cavdur et al., 2021) | ✓ | ✓ | S | Single | ✓ | ✓ | MILP | – | Heuristic | |||||||||
| (Gan, 2024) | ✓ | ✓ | ✓ | D | Multi | ✓ | ✓ | ✓ | ✓ | MILP | MATLAB | HFHA | ||||||
| (Ghasemi et al., 2022) | ✓ | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | Nonlinear | MATLAB | Metaheuristic/epsilon-constraint | ||||||
| (Haghi et al., 2017) | ✓ | ✓ | ✓ | S | Multi | ✓ | MILP | ILOG CPLEX | Exact method | |||||||||
| (Manopiniwes and Irohara, 2016) | ✓ | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | Nonlinear | GUROBI | Exact method | ||||
| (Meng et al., 2023) | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | Nonlinear | CPLEX | Heuristic/evolutionary | |||||
| (Pouraliakbari-Mamaghani et al., 2023) | ✓ | ✓ | S | Single | ✓ | ✓ | Nonlinear | GUROBI | Heuristic | |||||||||
| (Seraji et al., 2021) | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | D | Multi | ✓ | ✓ | ✓ | ✓ | MILP | GAM / CPLEX | GA | |||
| Wang et al. (2021) | ✓ | ✓ | S | Single | ✓ | ✓ | ✓ | MILP | CPLEX | Exact method | ||||||||
| (Turkeš et al., 2021) | ✓ | ✓ | S | Single | ✓ | ✓ | ✓ | ✓ | MILP | CPLEX | Metaheuristic/heuristic | |||||||
| (Wang et al., 2022) | ✓ | ✓ | S | Single | ✓ | ✓ | Nonlinear | CPLEX | PSO | |||||||||
| This work | ✓ | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | MILP | LINGO | Exact method | ||
| Authors | Objective function | Otherobjective | Fs | E | RT | D/S | Multi /singleobjective | Constraint | Mathmodel | Exactapproach | Solution algorithm | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cost | Time | Evacuation ofdistance | Capacity | Budget | Limitsite | Transportationmode | Items | Demand | ||||||||||
| ( | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | MILP | CPLEX | Augmencon epsilon-constraint | |||||||
| ( | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | ✓ | MILP | GAMS | GP | ||||
| ( | ✓ | ✓ | S | Single | ✓ | ✓ | MILP | – | Heuristic | |||||||||
| ( | ✓ | ✓ | ✓ | D | Multi | ✓ | ✓ | ✓ | ✓ | MILP | MATLAB | HFHA | ||||||
| ( | ✓ | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | Nonlinear | MATLAB | Metaheuristic/epsilon-constraint | ||||||
| ( | ✓ | ✓ | ✓ | S | Multi | ✓ | MILP | ILOG CPLEX | Exact method | |||||||||
| ( | ✓ | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | Nonlinear | GUROBI | Exact method | ||||
| ( | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | Nonlinear | CPLEX | Heuristic/evolutionary | |||||
| ( | ✓ | ✓ | S | Single | ✓ | ✓ | Nonlinear | GUROBI | Heuristic | |||||||||
| ( | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | D | Multi | ✓ | ✓ | ✓ | ✓ | MILP | GAM / CPLEX | GA | |||
| ✓ | ✓ | S | Single | ✓ | ✓ | ✓ | MILP | CPLEX | Exact method | |||||||||
| ( | ✓ | ✓ | S | Single | ✓ | ✓ | ✓ | ✓ | MILP | CPLEX | Metaheuristic/heuristic | |||||||
| ( | ✓ | ✓ | S | Single | ✓ | ✓ | Nonlinear | CPLEX | PSO | |||||||||
| ✓ | ✓ | ✓ | ✓ | ✓ | S | Multi | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | MILP | LINGO | Exact method | |||
Fs = facility & stock location; E = evacuation; RT = relief transportation; D = deterministic problem; S = stochastic problem; LP = linear programming; MILP = mixed integer linear programming; GA = genetic algorithm; GP = goal programming; PSO = particle swarm optimization; HFHA = hybrid frog hopping algorithm
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