Unmanned aerial vehicles mounted base stations (UAV-BSs) are expected to become one of the significant components of the Next Generation Wireless Networks (NGWNs). Rapid deployment, mobility, higher chances of unobstructed propagation path, and flexibility features of UAV-BSs have attracted significant attention. Despite, potentially, high gains brought by UAV-BSs in NGWNs, many challenges are also introduced by them. Optimal location assignment to UAV-BSs, arguably, is the most widely investigated problem in the literature on UAV-BSs in NGWNs. This paper presents a comprehensive survey of the literature on the location optimization of UAV-BSs in NGWNs. A generic optimization framework through a universal Mixed Integer Non-Linear Programming (MINLP) formulation is constructed and the specifications of its constituents are elaborated. The generic problem is classified into a novel taxonomy. Due to the highly challenging nature of the optimization problem a range of solutions are adopted in the literature which are also covered under the aforementioned classification. Furthermore, future research directions on UAV-BS location optimization in 5G and beyond non-terrestrial aerial communication systems are discussed.

In this study, an m-machine flexible robotic manufacturing cell consisting of CNC machines is considered. The flexibility of the machines leads to a new class of robot move cycles called the pure cycles. We first model the problem of determining the best pure cycle in an m-machine cell as a special travelling salesman problem in which the distance matrix consists of decision variables as well as parameters. We focus on two specific cycles among the huge class of pure cycles. We prove that, in most of the regions, either one of these two cycles is optimal. For the remaining regions we derive worst case performances of these cycles. We also prove that the set of pure cycles dominates the flowshop-type robot move cycles considered in the literature. As a design problem, we consider the number of machines in a cell as a decision variable. We determine the optimal number of machines that minimizes the cycle time for given cell parameters such as the processing times, robot travel times and the loading/unloading times of the machines.

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In this paper, we study the problem of two-machine, identical parts robotic cell scheduling with operational flexibility. We assume that every part to be processed has a number of operations to be completed in these two machines and both machines are capable of performing all of the operations. The decision to be made includes finding the optimal robot move cycle and the corresponding optimal allocation of operations to these two machines that jointly minimize the cycle time. We prove that with this definition of the problem 1-unit robot move cycles are no longer necessarily optimal and that according to the given parameters either one of the 1-unit robot move cycles or a 2-unit robot move cycle is optimal. The regions of optimality are presented. © 2004 Elsevier B.V. All rights reserved

In this study, we consider a flexible manufacturing cell (FMC) processing identical parts on which the loading and unloading of machines are made by a robot. The machines used in FMCs are predominantly CNC machines and these machines are flexible enough for performing several operations provided that the required tools are stored in their tool magazines. Traditional research in this area considers a flowshop type system. The current study relaxes this flowshop assumption which unnecessarily limits the number of alternatives. In traditional robotic cell scheduling literature, the processing time of each part on each machine is a known parameter. However, in this study the processing times of the parts on the machines are decision variables. Therefore, we investigated the productivity gain attained by the additional flexibility introduced by the FMCs. We propose new lower bounds for the 1-unit and 2-unit robot move cycles (for which we present a completely new procedure to derive the activity sequences of 2-unit cycles in a three-machine robotic cell) under the new problem domain for the flowshop type robot move cycles. We also propose a new robot move cycle which is a direct consequence of process and operational flexibility of CNC machines. We prove that this proposed cycle dominates all 2-unit robot move cycles and present the regions where the proposed cycle dominates all 1-unit cycles. We also present a worst case performance bound of using this proposed cycle. ᭧

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The focus of this study is the identical parts robotic cell scheduling problem with m machines under the assumption of process and operational flexibility. A direct consequence of this assumption is a new robot move cycle that has been overlooked in the existing literature. We prove that this new cycle dominates all classical robot move cycles considered in the literature for m ¼ 2. We also prove that changing the layout from an in-line robotic cell to a robot-centered cell reduces the cycle time of the proposed cycle even further, whereas the cycle times of all other cycles remain the same. For the m-machine case, we find the regions where the proposed cycle dominates the classical robot move cycles, and for the remaining regions present its worst case performance with respect to classical robot move cycles. Considering the number of machines as a decision variable, we also find the optimal number of machines that minimizes the cycle time of the proposed cycle.