Employing the Internet of Things to Attain Resilience Across Supply Chain

This paper investigates and analyses the features of sustainable warehousing by conducting a systematic literature review (SLR) to create a significant insight of the expanding and growing trends of sustainable warehousing, to fit perfectly within the net-zero supply chain strategies and adapting to the new value adding practices of Industry 5.0. Using a set of 65 publications, including journal papers, conference papers, and reviews, for the last 10 years, between 2013 and 2023, the SLR highlights and considers several green logistics areas that are essential to help redesign the features of sustainable warehouses. The paper also emphasizes the need for further research to develop new models for warehouses that can be implemented in the Industry 5.0 supply chain to achieve net-zero goals. In other words, the paper is trying to understand the current state of sustainable warehousing and identify areas where improvements can be made to make warehouses more sustainable and environmentally friendly, and to help the industry move towards a net-zero supply chain. Additionally, the paper is suggesting that there is a need for more research to be done to create new models for warehouses that can be applied in the Industry 5.0 supply chain, in order to reach net-zero goals

Systematic Literature Review Of Particle Swarm Optimization Implementation For Time-Dependent Vehicle Routing Problem

Time-dependent VRP (TDVRP) is one of the three VRP variants that have not been widely explored in research in the field of operational research, while Particle Swarm Optimization (PSO) is an optimization algorithm in the field of operational research that uses many variables in its application. There is much research conducted about TDVRP, but few of them discuss PSO's implementation. This article presented as a literature review which aimed to find a research gap about implementation of PSO to resolve TDVRP cases. The research was conducted in five stages. The first stage, a review protocol defined in the form of research questions and methods to perform the review. The second stage is references searching. The third stage is screening the search result. The fourth stage is extracting data from references based on research questions. The fifth stage is reporting the study literature results. The results obtained from the screening process were 37 eligible reference articles, from 172 search results articles. The results of extraction and analysis of 37 reference articles show that research on TDVRP discusses the duration of travel time between 2 locations. The route optimization parameter is determined from the cost of the trip, including the total distance traveled, the total travel time, the number of routes, and the number used vehicles. The datasets that are used in research consist of 2 types, real-world datasets and simulation datasets. Solomon Benchmark is a simulation dataset that is widely used in the case of TDVRP. Research on PSO in the TDVRP case is dominated by the discussion of modifications to determine random values of PSO variables

Impact of travel time uncertainties on the solution cost of a two-echelon vehicle routing problem with synchronization

Two-echelon vehicle routing problems which contain synchronization between vehicles can be deeply impacted by time uncertainty, because one vehicle's delay can propagate to other vehicles. In this paper, we evaluate the deterministic solution of such a problem based on simulated travel time scenarios. The information obtained by simulation is incorporated in the optimization procedure iteratively. Computational results show that the degree of synchronization in an instance is directly correlated with the potential improvements by reoptimization. We present findings on the number of travel time scenarios required to obtain a representative picture of the stochastic solutions. In addition, we demonstrate that time dependent travel times can be aggregated on a city-wide level and linearized as a function of free flow times without major loss of reliability

Last-mile logistics optimization in the on-demand economy

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