Capacitated Vehicle Routing Problem in mixed environment

In practical life situations, all information about the Vehicle routing problem may not be always readily available subject to the uncertainty present in real life. These uncertainties affect various parameters of the problem. For example, in real life situations, the customer demands are sometimes uncertain in nature, i.e., sometimes they are not known well in advance, and (or) sometimes they are not known precisely. Thus, solving these problems in such an environment can be challenging by using classical methods. Therefore, the development of Vehicle Routing Problem in uncertain environment is necessary. The books discuss various variants of Vehicle Routing problems in imprecise and random environment. CVRP with uncertain customers' demands, Mathematical model for CVRP with Imprecise Demands, Mathematical models for CVRP with fuzzy stochastic demand, Mathematical model for CVRP with intuitonistic fuzzy stochastic demand, CVRP with fuzzy stochastic edge weights and stochastic demands, Bi-level CVRP etc. Solution methodology for all the above models based on proposed algorithms. Experimental Results and comparison analysis for Benchmark instances.

Autorentext
Dr. V. P. Singh completed his PhD degree from IIT Kharagpur, India. His research interests include the Vehicle Routing Problem in a mixed environment and fuzzy Stochastic optimisation.Dr. Kirti Sharma earned her PhD degree from VNIT Nagpur, India. Her research interests include Vehicle Routing Problem, Optimisation Under Uncertainty.