Congestion and Pollution, Vehicle Routing Problem of a Logistics Provider in Thailand

Abstract

Aim and Objective:This study aims to minimise the travelling distance, operation cost in terms of fuel consumption, and CO 2 emissions. It introduces the Time-Dependency Pollution-Routing Problem (TDPRP) with the implementation of the time-dependency and emission model, including constraints such as the limitation of vehicle capacity and vehicle's speed during different time periods in Thailand. Furthermore, the time window constraint is applied for representing a more realistic model. The main objective is to minimise the total pollution generated because of transportation. Methods:The Genetic Algorithm (GA) and Tabu Search (TS) methods have been used to generate the optimal solution with a variety of experiments. The best solutions from all the experiments have been compared to the original solution in terms of the quality of the solution and the computation time. Results:The best solution was generated by using the TS method with 30,000 trials. The minimum of the total CO 2 emissions was 183.9846 kilograms produced from all of the vehicles during transportation, nearly half from the current transportation plan, which produced 320.94 kilograms of CO 2 emissions. Conclusion:The proposed model optimised both the route and schedules (multiple time periods) for a number of vehicles, for which the transportation during a fixed congestion period could be predicted to avoid traffic congestion and reduce the CO 2 emission. Future research is suggested to add other specific algorithms as well as constraints in order to make the model more realistic.at about 78% of the emissions from all transport modes [2]. CO 2 emissions are the result of fuel consumption and vehicle speed (travelling time). Transportation is the fastest-growing major contributor to global climate change, accounting for 23% of energy-related carbon dioxide (CO 2 ) emissions. Many experts foresee a three-to five-fold increase in CO 2 emissions from transportation in Asian countries by 2030 compared with emissions in 2000 if no changes are made to investment strategies and policies [3]. Traffic congestion directly affects the vehicle speed and the total time spent on the road. In addition, the fuel consumption rate depends on two factors, which are the speed of the vehicle and the load of the vehicle [4].

Residents’ Perception on an Inland Port Development in Northern Border of Peninsular Malaysia

“…The perception of the residents of Kubang Pasu is significant to the development of the inland port of Bukit Kayu Hitam, as it will directly affect them. Next, for the environmental factor, congestion in Bukit Kayu Hitam will cause air pollution and affect the health of the residents in Kubang Pasu (WHO, 2021; Alagesh, 2019; Moryadee et al, 2019;Zainuddin et al, 2019). Lastly, for the economic factor, Kedah is the second poorest state in Malaysia which has slow economic development and a widening income gap (Department of Statistics Malaysia, 2019; NST, 2019).…”