Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a hybrid algorithm, combining Biased-Randomized (BR) processes with an Iterated Local Search (ILS) meta-heuristic, to solve the Multi-Depot Vehicle Routing Problem (MDVRP). Our approach assumes a scenario in which each depot has unlimited service capacity and in which all vehicles are identical (homogeneous fleet). During the routing process, hover, each vehicle is assumed to have a limited capacity. Two BR processes are employed at different stages of the ILS procedure in order to: (a) define the perturbation operator, which generates new 'assignment maps' by associating customers to depots in a biased-random way --according to a distance-based criterion; and (b) generate 'good' routing solutions for each customers-depots assignment map. These biased-randomization processes rely on the use of a pseudo-geometric probability distribution. Our approach does not need from fine-tuning processes which usually are complex and time consuming. Some preliminary tests have been carried out already with encouraging results.
['Angel A. Juan', 'Barry B. Barrios', 'Sergio González-Martín', 'Javier Faulin', 'Mariana E. Cóccola', 'Tolga Bektas']
I am writing a research paper on a idea Combining biased randomization with meta-heuristics for solving the multi-depot vehicle routing problem
[{"from": "human", "value": "I am writing a research paper on a idea Combining biased randomization with meta-heuristics for solving the multi-depot vehicle routing problem"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  proposes a hybrid algorithm, combining Biased-Randomized (BR) processes with an Iterated Local Search (ILS) meta-heuristic, to solve the Multi-Depot Vehicle Routing Problem (MDVRP). Our approach assumes a scenario in which each depot has unlimited service capacity and in which all vehicles are identical (homogeneous fleet). During the routing process, hover, each vehicle is assumed to have a limited capacity. Two BR processes are employed at different stages of the ILS procedure in order to: (a) define the perturbation operator, which generates new 'assignment maps' by associating customers to depots in a biased-random way --according to a distance-based criterion; and (b) generate 'good' routing solutions for each customers-depots assignment map. These biased-randomization processes rely on the use of a pseudo-geometric probability distribution. Our approach does not need from fine-tuning processes which usually are complex and time consuming. Some preliminary tests have been carried out already with encouraging results."}]