Optimizing last mile delivery using public transport with multiagent based control
Rajeshwari, Chatterjee (2016)
Diplomityö
Rajeshwari, Chatterjee
2016
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2016082422966
https://urn.fi/URN:NBN:fi-fe2016082422966
Tiivistelmä
The majority of research work carried out in the field of Operations-Research uses
methods and algorithms to optimize the pick-up and delivery problem. Most studies aim
to solve the vehicle routing problem, to accommodate optimum delivery orders,
vehicles etc. This paper focuses on green logistics approach, where existing Public
Transport infrastructure capability of a city is used for the delivery of small and medium
sized packaged goods thus, helping improve the situation of urban congestion and
greenhouse gas emissions reduction. It carried out a study to investigate the feasibility
of the proposed multi-agent based simulation model, for efficiency of cost, time and
energy consumption. Multimodal Dijkstra Shortest Path algorithm and Nested Monte
Carlo Search have been employed for a two-phase algorithmic approach used for
generation of time based cost matrix. The quality of the tour is dependent on the
efficiency of the search algorithm implemented for plan generation and route planning.
The results reveal a definite advantage of using Public Transportation over existing
delivery approaches in terms of energy efficiency.
methods and algorithms to optimize the pick-up and delivery problem. Most studies aim
to solve the vehicle routing problem, to accommodate optimum delivery orders,
vehicles etc. This paper focuses on green logistics approach, where existing Public
Transport infrastructure capability of a city is used for the delivery of small and medium
sized packaged goods thus, helping improve the situation of urban congestion and
greenhouse gas emissions reduction. It carried out a study to investigate the feasibility
of the proposed multi-agent based simulation model, for efficiency of cost, time and
energy consumption. Multimodal Dijkstra Shortest Path algorithm and Nested Monte
Carlo Search have been employed for a two-phase algorithmic approach used for
generation of time based cost matrix. The quality of the tour is dependent on the
efficiency of the search algorithm implemented for plan generation and route planning.
The results reveal a definite advantage of using Public Transportation over existing
delivery approaches in terms of energy efficiency.