Many application problems are formulated as nonlinear binary programming models which are hard to be solved using exact algorithms especially in large dimensions. One of these practical applications is to optimally distribute protective materials for the newly emerged COVID-19. It is defined for a decision-maker who wants to choose a subset of candidate hospitals comprising the maximization of the

Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses for airline activities. A nonlinear mixed binary mathematical programming model for the airline fuel task is presented to minimize the total cost of refueling in an entire flight

The reduction of the high peak-to-average-power ratio (PAPR) is important to the efficiency of the orthogonal frequency division multiplexing (OFDM) technique. Excessive PAPR contributes to non-linear clipping induced harmonic distortions that reduce system reliability. In this article, a new technique for decreasing the high PAPR in OFDM with minimum effects on the system performance is proposed

During last two decades, Differential Evolution (DE) proved to be one of the most popular and successful evolutionary algorithms for solving global optimization problems over continuous space. Proposing new mutation strategies to improve the optimization performance of (DE) is considered a significant research study. In DE, mutation operation plays a vital role in the performance of the algorithm

Future and current cellular networks encounter an unprecedented growth of mobile devices traffic, imposing various critical challenges that should be thoroughly addressed. Catering for such enormous amount of traffic demand via cellular networks significantly increases the network congestion and degrades the achievable quality of service (QoS). Thus, traffic offloading has been suggested to tackle

For the solar photovoltaic (PV) system to operate efficiently, it is necessary to effectively establish an equivalent model of PV cell and extract the relevant unknown model parameters accurately. This paper introduces a new metaheuristic algorithm, i.e., gaining-sharing knowledge based algorithm (GSK) to solve the solar PV model parameter extraction problem. This algorithm simulates the process

Long-Term Evolution (LTE) technology is expected to shift some of its transmissions into the unlicensed band to overcome the spectrum scarcity problem. Nevertheless, in order to effectively use the unlicensed spectrum, several challenges have to be addressed. The most important of which is how to coexist with the incumbent unlicensed WiFi networks. Incorporating the "intelligence"component into

Filter bank multi-carrier (FBMC) is considered a promising alternative to the Orthogonal Frequency Division Multiplexing (OFDM) scheme. It improves spectral efficiency by eliminating the need for cyclic prefix while attenuating interference due to the robustness of the out-of-band emission. In this work, we present a framework, and the performance evaluation of FBMC is a multi-carrier modulation

Quantum cryptography is a promising technology that achieves unconditional security, which is essential to a wide range of sensitive applications. In contrast to optical fiber, the free-space optical (FSO) link is efficiently used as a quantum channel without affecting the polarization of transmitted photons. However, the FSO link has several impairments, such as atmospheric turbulence and

In this paper, we study a wireless powered cellular network (WPCN) supported with network coding capability. In particular, we consider a network consisting of k cellular users (CUs) served by a hybrid access point (HAP) that takes over energy transfer to the users on top of information transmission over both the uplink (UL) and downlink (DL). Each CU has k+1 states representing its communication