An Advanced System to Enhance and Optimize Delivery Operations in a Smart Logistics Environment

Abstract

Optimization of order dispatch operations and delivery time prediction is a major concern in supply chains, mainly for e-commerce, which requires the implementation of advanced solutions to reduce delivery time, minimize costs and maximize customer satisfaction. In practice, they fail to warrant scalable and sustainable solutions as the numbers of orders become larger. For that, proper prediction and optimization for delivery operations are required for optimal logistics management. This paper presents an advanced logistics service, which warrants dynamic coordination among all the actors in the smart logistics environment. The proposed advanced shipping system consists of two main parts: the delivery prediction model to compute the expected arrival time, and a hybrid optimization model to tackle path issues. We demonstrate that the advanced system consistently outperforms conventional standard dispatching methods, which means that the proposed approach effectively contributes to optimizing the distribution chain and reducing costs.

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

“…For each tourist who has different travel preferences, the Pareto ant colony optimization algorithm is applied to design a personalized travel route that satisfies the tourists. Issaoui et al [14] solve the complex tourist route optimization problem by using the heuristic shortest path algorithm, and the route planning works well. Goel and Maini [15] used an improved ant colony algorithm to improve the quality of the global optimal solution, established a mathematical model with road factor, waiting for factor and interest factor as influencing factors in scenic spots, and analyzed the application of the ant colony algorithm in route planning with tourist satisfaction as evaluation criteria; the results proved that the improved ant colony algorithm solves the road map based on tourist satisfaction; and the effect is significant compared with the previous tourist satisfaction.…”

Recent Technological Progress to Empower Smart Manufacturing: Review and Potential Guidelines

“…Studies have shown that more than 70% of manufacturers believe that smart technologies such as the Internet of Things; Big data analytics; machine learning and augmented reality are integral to their future. Indeed, according to McKinsey, Industry, 4.0 could yield $3.7 trillion in value for manufacturers and suppliers by 2025, but only 30% of companies are currently benefiting from Industry 4.0 solutions at scale [156].…”

Competitiveness of the Shared Economy Model for Sustainable Management of Logistics Systems

“…However, there are some risks that require evaluation. The providing framework developed could integrate smart services and technologies as well as enable the elimination of risks [10][11][12][13][14][15].…”