We show that the 2 × interference network, i.e., multihop network formed by concatenation of two two-user channels achieves min-cut outer bound value DoF, for almost all values channel coefficients, both time-varying or fixed-channel coefficients. The key to this result is a new idea, called aligned neutralization, provides way align terms over each hop in manner allows them be canceled air at last hop.

The job-shop scheduling problem (JSSP) is a challenging and optimization in the industry engineering, which relates to work efficiency operational costs of factories. completion time all jobs most commonly considered objective existing work. However, factories focus on both cost objectives, including time, total tardiness, advance production cost, machine loss. Therefore, this article first proposes many-objective JSSP that considers these five objectives make model more practical reflect...

In high dimensional environment, the interaction among particles significantly affects their movements in searching vast solution space and thus plays a vital role assisting particle swarm optimization (PSO) to attain good performance. To this end, paper designs random contrastive (RCI) strategy for PSO, resulting RCI-PSO, tackle large-scale problems (LSOPs) effectively efficiently. Unlike existing mechanisms low-dimensional problems, RCI randomly chooses several different peers from current...

Local search has been regarded as a promising technique in multimodal algorithms to refine the accuracy of found multiple optima. However, how execute local operations precisely on global optima and avoid meaningless or similar areas is still challenge. In this paper, we propose novel based individual information from two aspects, termed fitness distance (FDLS). The can ineffective optima, while areas. These kinds act different roles complement each other, which ensures that executed...

As Internet of Things (IoT) networks grow larger, the amount data that needs to be collected at a fusion center increases rapidly. However, collection based solely on multi-hop routing between IoT sensor nodes or unmanned aerial vehicles (UAVs) visiting all may not scalable as network size increases. To overcome such limitation, general multi-UAV-enabled aggregation and method utilizing both UAV is proposed minimize weighted sum transmission energy traveling UAVs. An efficient joint...

Two distinct, but overlapping, networks that operate at the same time, space, and frequency is considered. The first network consists of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> randomly distributed primary users, which form an ad hoc network. second again xmlns:xlink="http://www.w3.org/1999/xlink">m</i> secondary users or cognitive users. have priority access to spectrum do not need change their communication protocol in presence...

We consider a wireless device-to-device network, where n nodes are uniformly distributed at random over the network area. let each node caches M files from library of size m ≥ M. Each in requests file independently random, according to popularity distribution, and is served by other having requested their local cache via (possibly) multihop transmissions. Under classical "protocol model" networks, we characterize optimal per-node capacity scaling law for broad class heavy-tailed...

Expensive optimization problems (EOPs) are common in industry and surrogate-assisted evolutionary algorithms (SAEAs) have been developed for solving them. However, many EOPs not only expensive objective but also constraints, which evaluated through distributed ways. We define this kind of as constrained (DECOPs). The characteristic DECOPs leads to the asynchronous evaluation both constraints. Though some researchers studied objectives, constraints has gained much attention. Therefore,...

Feature selection, which aims to improve the classification accuracy and reduce size of selected feature subset, is an important but challenging optimization problem in data mining. Particle swarm (PSO) has shown promising performance tackling selection problems, still faces challenges dealing with large-scale Big Data environment because large search space. Hence, this paper proposes a bi-directional fixation (BDFF) framework for PSO provides novel idea space selection. BDFF uses two...

Optimization problems become increasingly complicated in the era of big data and Internet Things, which significantly challenges effectiveness efficiency existing optimization methods. To effectively solve this kind problems, paper puts forward a stochastic cognitive dominance leading particle swarm algorithm (SCDLPSO). Specifically, for each particle, two personal best positions are first randomly selected from those all particles. Then, only when position is dominated by at least one ones,...

Sudoku puzzles are not only popular intellectual games but also NP-hard combinatorial problems related to various real-world applications, which have attracted much attention worldwide. Although many efficient tools, such as evolutionary computation (EC) algorithms, been proposed for solving puzzles, they still face great challenges with regard hard and large instances of puzzles. Therefore, efficiently solve this paper proposes a genetic algorithm (GA)-based method novel local search...

Abstract High-dimensional optimization problems are increasingly pervasive in real-world applications nowadays and become harder to optimize due interacting variables. To tackle such effectively, this paper designs a random elite ensemble learning swarm optimizer (REELSO) by taking inspiration from human observational theory. First, partitions particles the current into two exclusive groups: group consisting of top best non-elite containing rest based on their fitness values. Next, it...

This paper analyzes the impact and benefits of infrastructure support in improving throughput scaling networks $n$ randomly located wireless nodes. The uses multi-antenna base stations (BSs), which number BSs antennas at each BS can scale arbitrary rates relative to $n$. Under model, capacity laws are analyzed for both dense extended networks. Two BS-based routing schemes first introduced this study: an infrastructure-supported single-hop (ISH) protocol with multiple-access uplink broadcast...

Particle swarm optimization (PSO) has exhibited well-known feasibility in problem optimization. However, its performance still encounters challenges when confronted with complicated problems many local areas. In PSO, the interaction among particles and utilization of communication information play crucial roles improving learning effectiveness diversity particles. To promote particles, this paper proposes a stochastic triad topology to allow each particle communicate two random ones via...

We consider reconfigurable intelligent surface (RIS) aided sixth-generation (6G) terahertz (THz) communications for indoor environment in which a base station (BS) wishes to send independent messages its serving users with the help of multiple RISs. For environment, various obstacles such as pillars, walls, and other objects can result no line-of-sight signal path between BS user, significantly degrade performance. To overcome limitation THz communication, we firstly optimize placement RISs...

We consider a multi-user multi-server mobile edge computing (MEC) system, in which users arrive on network randomly over time and generate computation tasks, will be computed either locally their own devices or offloaded to one of the MEC servers. Under such dynamic environment, we propose novel task offloading policy based hybrid online-offline learning, can efficiently reduce overall delay energy consumption only with information available at nearest servers from each user. provide...

Tourism is an important industry sector that requires tour companies to plan multiple routes for different groups, which called multi-route planning. This paper focuses on planning, can improve the economic benefit and allocation efficiency of resources. The main contributions this are threefold. First, we propose a novel planning model captures real-world tourism scenario practical constraints. We also define four typical constraints classify them into soft hard Second, develop matrix-based...

Infrared-based detection of small targets on ships is crucial for ensuring navigation safety and effective maritime traffic management. However, existing ship target models often encounter missed detections struggle to achieve both high accuracy real-time performance at the same time. Addressing these challenges, this study presents Light-YOLO, a lightweight model detection. Within YOLOv8 network architecture, Light-YOLO replaces conventional convolutions with snake convolutions, effectively...