Abstract
During the last decade, tremendous focus has been given to sustainable logistics practices to overcome environmental concerns of business practices. Since transportation is a prominent area of logistics, a new area of literature known as Green Transportation and Green Vehicle Routing has emerged. Vehicle Routing Problem (VRP) has been a very active area of the literature with contribution from many researchers over the last three decades. With the computational constraints of solving VRP which is NP-hard, metaheuristics have been applied successfully to solve VRPs in the recent past. This is a threefold study. First, it critically reviews the current literature on EMVRP and the use of metaheuristics as a solution approach. Second, the study implements a genetic algorithm (GA) to solve the EMVRP formulation using the benchmark instances listed on the repository of CVRPLib. Finally, the GA developed in Phase 2 was enhanced through machine learning techniques to tune its parameters. The study reveals that, by identifying the underlying characteristics of data, a particular GA can be tuned significantly to outperform any generic GA with competitive computational times. The scrutiny identifies several knowledge gaps where new methodologies can be developed to solve the EMVRPs and develops propositions for future research.
Highlights
The overall objective of this study is to develop a set of genetic algorithms to solve the Energy Minimizing VRP (EMVRP) and apply machine learning techniques to tune the developed algorithms to enhance the quality of the solutions
As mentioned in a previous section, the data for the experiment is taken from CVRPLib
The EMVRP is the problem which looks at finding routes of vehicles which use the least amount of energy when serving a set of cities or customers
Summary
Vehicle Routing Problem (VRP) can be described as the problem of finding optimal routes for delivery or collection from one to many depots to many customers who are geographically distributed. This problem has been the core for many operations research problems and has many variations. With the focus on sustainable business practices, a novel category of VRP has emerged, known as Green VRP. In this category, the objectives are different from original VRP where it minimizes the travelled distance reducing the cost. It has been identified that energy consumption has a direct impact on carbon dioxide emission
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