Underwater Acoustic Sensor Network Data Optimization with Enhanced Void Avoidance and Routing Protocol

Deployment of a multi-hop underwater acoustic sensor network (UASN) in a larger region presents innovative challenges in reliable data communications and survivability of network because of the limited underwater interaction range or bandwidth and the limited energy of underwater sensor nodes. UASNs are becoming very significant in ocean exploration applications, like underwater device maintenance, ocean monitoring, ocean resource management, pollution detection, and so on. To overcome those difficulties and attains the purpose of maximizing data delivery ratio and minimizing energy consumption of underwater SNs, routing becomes necessary. In UASN, as the routing protocol will guarantee effective and reliable data communication from the source node to the destination, routing protocol model was an alluring topic for researchers. There were several routing techniques devised recently. This manuscript presents an underwater acoustic sensor network data optimization with enhanced void avoidance and routing (UASN-DAEVAR) protocol. The presented UASN-DAEVAR technique aims to present an effective data transmission process using proficient routing protocols. In the presented UASN-DAEVAR technique, a red deer algorithm (RDA) is employed in this study. In addition, the UASN-DAEVAR technique computes optimal routes in the UASN. To exhibit the effectual results of the UASN-DAEVAR technique, a wide spread experimental analysis is made. The experimental outcomes represented the enhancements of the UASN-DAEVAR model

Cross-docking: A systematic literature review

This paper identifies the major research concepts, techniques, and models covered in the cross-docking literature. A systematic literature review is conducted using the BibExcel bibliometric analysis and Gephi network analysis tools. A research focus parallelship network (RFPN) analysis and keyword co-occurrence network (KCON) analysis are used to identify the primary research themes. The RFPN results suggest that vehicle routing, inventory control, scheduling, warehousing, and distribution are most studied. Of the optimization and simulation techniques applied in cross-docking, linear and integer programming has received much attention. The paper informs researchers interested in investigating cross-docking through an integrated perspective of the research gaps in this domain. This paper systematically reviews the literature on cross-docking, identifies the major research areas, and provides a survey of the techniques and models adopted by researchers in the areas related to cross-docking

Internet of Things in urban waste collection

Nowadays, the waste collection management has an important role in urban areas. This paper faces this issue and proposes the application of a metaheuristic for the optimization of a weekly schedule and routing of the waste collection activities in an urban area. Differently to several contributions in literature, fixed periodic routes are not imposed. The results significantly improve the performance of the company involved, both in terms of resources used and costs saving

Application of Tabu Search to Scheduling Trucks in Multiple Doors Cross-Docking Systems

RÉSUMÉ : Cette recherche focus sur l’amélioration des cross-dockings en vue d’augmenter les niveaux de performance du service et de réduire les coûts. l’algorithme de la recherche avec tabous est étudiée pour trouver la séquence optimale d’entrée et sortie des remorques au cross-docking. L’objectif de cette recherche est de maximiser le nombre total de transferts directs entre le fournisseur et une destination finale commune de livraison. Dans les stratégies de distribution actuelles, l’objectif est de synchroniser les chaines du fabricant et du client. Le cross-docking implique de recevoir les produits d’un fournisseur pour plusieurs clients et d’occasionnellement consolider cela avec les produits d’autres fournisseurs pour des destinations finales de livraison communes. En résumé, l’approche examinée dans cette recherche donne une occasion significative pour l’amélioration des opérations au Cross-docking par la réduction du stockage des produits.----------ABSTRACT : Today’s supply chain management performance has been affected by continuously increasing pressure of market forces. The pressure of market includes demands on increased flow of products and throughput with less amount of storage, also customers demand for more products with lower operational costs and more value-added services provided to customers. Supply chain is responsible in cost reduction and service levels increase by providing transshipments across its members. However supply chain has to face fluctuations of demands with the short available lead times. Physical problem of warehouse limitations and also inventory costs and shipping affect the performance of supply chain. In today’s distribution strategies, the main goal is to provide a synchronization of customer chains and the suppliers. The objective is to reduce the inventory buffering between customers and suppliers. The idea of cross-docking is to receive different goods from a manufacturer for several end destinations and possibly consolidate the goods with other manufacturer’s items for common final customers; then ship them in the earliest possible time. The focus of this research effort is to improve cross-dock operations with the goal of increasing the service performance levels and reducing costs. Specifically, metaheuristics algorithm of Tabu search is investigated for finding optimal sequence of incoming and outgoing trailers at cross-docks. This thesis reviews available research literature on cross-dock operations. Tabu search for the truck scheduling problem is presented along with results. Tabu search algorithm is investigated for the truck scheduling problem in the multiple doors cross-docking with unknown incoming and outgoing sequences. The objective of this research is to maximize the total direct transfer of products from a supplier to common final delivery destinations. The algorithm is implemented in C++ and analyzed using different problem instances. The results gained from algorithm of Tabu search are compared with other iterative heuristic descent method. The results indicate that the Tabu search performs significantly better than the descent method for large problem instances. In general, the results present that a metaheuristic algorithm of Tabu search for multiple or single door cross-docking offers thelargest potential for improvement. In summary, the approach explored in this research offers significant opportunity to improve cross-dock operations through reducing storage of products

Truck scheduling problem in a cross-docking system with release time constraint

Abstract In a supply chain, cross-docking is one of the most innovative systems for ameliorating the operational performance at distribution centers. Cross-docking is a logistical strategy in which freight is unloaded from inbound trucks and (almost) directly loaded into outbound trucks, with little or no storage in between, thus no inventory remains at the distribution center. In this study, we consider the scheduling problem of inbound and outbound trucks with multiple dock doors, aiming at the minimization of the makespan. The considered scheduling problem determines where and when the trucks must be processed; also due to the interchangeability specification of products, product assignment is done simultaneously as well. Inbound trucks enter the system according to their release times', however, there is no mandatory time constraint for outbound truck presence at a designated stack door; they should just observe their relative docking sequences. Moreover, a loading sequence is determined for each of the outbound trucks. In this research, a mathematical model is derived to find the optimal solution. Since the problem under study is NP-hard, a simulated annealing algorithm is adapted to find the (near-) optimal solution, as the mathematical model will not be applicable to solve largescale real-world cases. Numerical examples have been done in order to specify the efficiency of the metaheuristic algorithm in comparison with the results obtained from solving the mathematical model