An extended version of adaptive large neighborhood search for a relief commodities distribution network design under uncertainty

Natural and technology-induced disasters have posed significant threats to human life all around the world caused many damages losses so far. The current study addresses a location-routing problem make an efficient timely distribution plan in response possible earthquake. This considers uncertainty such parameters as demand, access routes, travel time, number of available vehicles. To deal with these uncertainties, stochastic programming (SP) is performed while objective function minimize time carrying relief commodities (RCs) affected areas. coded CPLEX solver obtain optimal solutions small-scale problems, adaptive large neighborhood search (ALNS) proposed solve mixed-integer linear formulas for large-scale problems. validate formulation evaluate performance ALNS, several types tests are devised. shows efficiency two other metaheuristic algorithms, Genetic algorithm (GA) simulated annealing (SA), used well. results calculations suggest satisfactory suggested effectiveness model desirable delivery humanitarian aids