Logistics 4.0 is very important to the current business world. It is expected to revolutionize a lot of business aspects. However, there is no clear definition for Logistics 4.0 till now. Due to its important impact on businesses nowadays, this work aims at reaching a definition for Logistics 4.0. The process of defining Logistics 4.0 is performed through reviewing the historical background between industry and logistics, in addition to identifying different trends of logistics. Through a systematic literature review, historical background on the relationship between previous industrial revolutions and their associated Logistics changes, this work proposes a novel concept, and hence, a definition to the current logistics and supply chain world, in light of Industry 4.0.

To ensure robustness in wireless networks, monitoring the network state, performance and functioning of the nodes and links is crucial, especially for critical applications. This paper targets Internet of Things (IoT) networks. In the IoT, devices (things) are vulnerable due to security risks from the Internet. Moreover, they are resource-constrained and connected via Lossy links. This work addresses the optimized scheduling of the monitoring role between the embedded devices in IoT networks. The objective is to minimize energy consumption and communication overhead of monitoring, for each node. Several subsets of the potential monitoring nodes are generated by solving a minimal Vertex Cover Problem with Constraint Generation. Assuming periodical functioning, Vertex Covers are optimally assigned to time periods in order to distribute the monitoring role throughout the entire network. The assignment of Vertex Covers to periods is modeled as a Multi-objective Generalized Assignment Problem. To further optimize the energy consumption of the monitors, they are sequenced across time periods to minimize the state transitions of nodes. This part of the problem is modeled as a Traveling Salesman Path Problem. The proposed model is tested on randomly generated instances and the experimental results illustrate its effectiveness to optimize the scheduled monitoring for fault tolerance in IoT networks.

High quality education should be the top priority for any nation seeking prosperity. This paper aims to present a conceptual model for e-learning system for developing countries. This is achieved adopting an object-oriented approach and Unified Modeling Language (UML). The functional and dynamic views of the system are presented and explained within this framework. The functional system includes Use Case diagrams and activity diagrams which are developed based on predefined functional requirements of the system. Furthermore, in the dynamic view of the system, interaction diagrams are developed and explained in detail. The proposed models are a step towards efficient implementation of a complete e-learning system in developing countries.

The vehicle routing problem (VRP) is one of the important problems that has been examined extensively over the past decades. The problem holds a central position within the fields of transportation logistics and supply chain management. Due to the NP-hard nature of the problem, many researchers have developed several heuristics and metaheuristics to solve the problem. This research proposes a hybrid bat algorithm to solve the VRP. The algorithm employs the Bat algorithm hybridized with a modified kmeans algorithm. The proposed solution technique adopts the methodology of cluster first route second to decompose the original VRP into traveling sales man problems (TSPs) with reduced complexity. Benchmark test instances from the literature are used to prove the efficiency of the proposed hybrid algorithm.