Heuristic approaches to address vehicle routing problem in the Iot-based waste management system

Nowadays, population growth and urban development lead to having an efficient waste management system (WMS) based on recent advances and trends. Alongside all functions and procedures in these systems, the waste collection plays a significant role. This study proposes a two-echelon WMS to minimize operational costs and environmental impact by utilizing the industry 4.0 concept. Both models utilize modern traceability Internet of Thing-based devices to compare real-time information of waste level in bins and separation centers with the threshold waste level (TWL) parameter. The first model optimizes the operational cost and CO2 emission of collecting waste from bins to the separation center by considering the time windows. A capacitated vehicle routing problem is designed as a later model-based to minimize the cost of waste transferring to recycling centers. In addition, to find the optimal solution, recent meta-heuristic algorithms are employed, and several novel heuristics based on the problem's specifications are developed. Furthermore, the developed heuristics methods are utilized to generate the initial feasible solutions in meta-heuristics and compared with random ones. The performance of the proposed algorithms is probed, and Best Worst Method (BWM) is applied to rank the algorithms based on relative percentage deviation, relative deviation index and hitting time.

Automated summary

This study proposes a two-echelon waste management system (WMS) based on industry 4.0 concept to minimize operational costs and environmental impact. The system utilizes modern traceability Internet of Things devices to compare real-time waste levels with the threshold waste level parameter. The first model optimizes the operational cost and CO2 emission of waste collection, while the later model aims to minimize the cost of waste transferring to recycling centers. Recent meta-heuristic algorithms are employed to find the optimal solution, and novel heuristics based on the problem's specifications are developed.