Optimization of Urban Waste Transportation Route Based on Genetic Algorithm

Abstract

Under the normal conditions of the new economy, people’s living standards have improved; the amount of urban domestic waste has increased suddenly; and the differentiation of waste has become more and more complicated. However, the garbage transportation method at this stage has been difficult to meet the needs of reality. Therefore, it is particularly urgent to reform the original and simple treatment methods and adopt the latest and more reasonable garbage transportation. The urban waste transportation route optimization described in this article is quite complicated in the specific problems faced in the optimization of the urban domestic waste transportation route. This paper proposes to combine computer science to study the system optimization model and combine information management and other disciplines to develop and apply research on the dynamic management software of urban waste logistics systems. In the modern service industry, logistics occupies an important position. The optimization of urban waste transportation routes based on genetic algorithms also promotes the development of high-end modern service industries and is an important task to promote urban development and maintained hygiene and improve the healthcare of the citizens. The optimization of urban waste transportation routes is conducive to creating a clean and tidy urban environment.

A Review on Intelligent Control Theory and Applications in Process Optimization and Smart Manufacturing

“…GAs are specialized evolutionary algorithms that replicate the natural selection process to discern optimal solutions. The applications of GAs span numerous domains: robotics (e.g., path planning [254] and grasping [255]), image and signal processing (like image segmentation [256] and feature extraction [257]), game theory (optimal strategy for playing games [258]), bioinformatics (protein structure prediction [259], DNA sequencing [260]), economics (optimal portfolio of stocks [261], optimizing the allocation of resources in a market [262]), transportation and logistics (optimize transportation routes [263], optimizing airline schedules [264]). The steps of genetic algorithm are shown in Figure 19.…”

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

“…As such, this problem has been performed keeping in view various goals. The minimization of the route distance taken by a garbage tuck has been performed by the authors in [27][28][29][30][31]. The aim in this case is to determine a route for garbage collection vehicles that minimizes the total distance traveled by the them.…”

“…The aim in this case is to determine a route for garbage collection vehicles that minimizes the total distance traveled by the them. Zhang et al [31] consider multi-vehicle allocation while considering the single objective of minimizing route distance. Wei et al [32] use the Artificial Bee Colony algorithm to determine garbage collection routes resulting in the minimum emission of CO 2 .…”

“…Self-collected/Presented/Generated [27][28][29]31,33,35,37] Government Agency [34,36] Dataset Capacitated VRP datasets [38] by [30], Capacitated VRP Instances [39] by [32]…”

Quantifying odour impacts from aged organic waste to be considered as a priority constraint in route optimization for waste collection trucks

“…This obvious failure in design is due to poor scheduling of bin visits caused by an optimization algorithm that was strictly designed to program trucks to hit certain locations along their shortest path, regardless of the volume of waste in the bins, leading to collection of empty and half empty bins. One way of prioritizing the status of the solid waste bins over the shortening of collection routes is to set the volume of collected solid waste as the main performance indicator (Abdallah et al, 2019; Catania and Ventura, 2014; Fan et al, 2010; Son, 2014; Zhang et al, 2022), through either static or dynamic modelling. This will only make sure that no accumulation above a predetermined volume will occur for all bins regardless of the waste characteristics and age.…”