The urban population increase results in more supply chain operations in these areas, which leads to increased energy consumption and environmental problems. In a new paper, about a multi-objective approach for optimizing city logistics considering energy efficiency the authors describe an optimization model of a multi-echelon collection and distribution system, focusing on downtown areas and energy efficiency, sustainability, and emission reduction.
After a systematic literature review, this paper introduces a mathematical model of collection and distribution problems, including parcel delivery, municipal waste collection, home delivery services, and supply of supermarkets and offices. The object of the optimization model is twofold:
- to design the optimal structure of the multi-echelon collection and distribution system, including layout planning and the determination of required transportation resources, like e-cars, e-bikes, and the use of public transportation;
- to optimize the operation strategy of the multi-echelon supply chain, including resource allocation and scheduling problems.
The model includes a wide range of objective functions, like the minimization of transportation distance, energy consumption, and the emission of greenhouse gases, while various constraints like the capacity of resources, service level, availability and suitability of material handling resources, and available energy in high voltage batteries or fuel cells are taken into consideration. The described methodology shows that the transformation of conventional city logistics solutions into an e-vehicle based multi-echelon supply chain significantly decreases energy consumption and emission, while service level and flexibility are likely to be increased. Depending on the source of electric energy generation, different emission reduction can be realized.
Next, a heuristic approach is described, whose performance is validated with common benchmark functions, such as metaheuristic evaluation. The scenario analysis demonstrates the application of the described model and shows the optimal layout, resource allocation, and operation strategy focusing on energy efficiency.