Short-term hydro-thermal scheduling aims to obtain optimal generation scheduling of hydro and thermal units for a one-day or a one-week scheduling time horizon. The main goal of the problem is to minimize total operational cost considering a series o...
This paper presents a discrete particle swarm optimization (DPSO) algorithm with heterogeneous (non-uniform) parameter values for solving the dynamic traveling salesman problem (DTSP). The DTSP can be modeled as a sequence of static sub-problems, eac...
To further improve the path planning of the mobile robot in complex dynamic environments, this paper proposes an enhanced hybrid algorithm by considering the excellent search capability of the ant colony optimization (ACO) for global paths and the ad...
This paper proposes a dynamic vehicle routing problem (DVRP) model with fuzzy customer responses and suggests optimal routing strategies. Most DVRP studies have focused on how to create a new route upon the occurrence of dynamic situations such as un...
The dynamic lot-sizing problem under a time-varying environment considers new features of the production system where factors such as production setup cost, unit inventory-holding cost, and unit price of manufacturing resources may vary in different...
In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The w...
Remora Optimization Algorithm (ROA) is a recent population-based algorithm that mimics the intelligent traveler behavior of Remora. However, the performance of ROA is barely satisfactory; it may be stuck in local optimal regions or has a slow converg...
As a new delivery mode, the collaborative delivery of packages using trucks and drones has been proven to reduce delivery costs and delivery time. To cope with the huge cost challenges brought by strict time constraints and ever-changing customer ord...
This work proposes a new approach to improve swarm intelligence algorithms for dynamic optimization problems by promoting a balance between the transfer of knowledge and the diversity of particles. The proposed method was designed to be applied to th...
Street delivery faces significant challenges due to outdated road infrastructure, which was not designed to handle current vehicle volumes, leading to congestion and inefficiencies, especially in last-mile delivery. Integrating drones into the delive...
The urban logistics delivery problem is a complex path planning task that must balance logistics costs and time-window-based quality of service under time-varying traffic conditions. Most urban logistics models assume constant travel speeds, thereby...
The study of unmanned aerial vehicle (UAV) coverage path planning is of great significance for ensuring maritime situational awareness and monitoring. In response to the problem of maritime multi-region coverage surveillance in complex obstacle envir...
Tourism activities essentially represent the interaction between crowds and attractions. Thus, crowd dynamics are critical to the quality of the tourism experience in personalized tour recommendations. In order to generate dynamic, personalized tour...
A growing number of researchers are interested in deploying unmanned surface vehicles (USVs) in support of ocean environmental monitoring. To accomplish these missions efficiently, multiple-waypoint path planning strategies for survey USVs are still...
The widespread adoption of Unmanned Aerial Vehicles (UAVs) in civilian domains, such as airport security and critical infrastructure protection, has introduced significant safety risks that necessitate effective countermeasures. High-Energy Laser Sys...
With increasingly diverse customer demands and the rapid growth of the new energy logistics industry, establishing a sustainable and responsive logistics network is critical. In a multi-depot logistics network, adopting collaborative distribution and...
The development of electric quarry transport puts a significant strain on local power grids, leading to sharp peaks in consumption and degradation of power quality. Existing methods of peak smoothing, such as generation control, virtual power plants,...
The torque ripples in a switched reluctance motor (SRM) are minimized via an optimal adaptive dynamic regulator that is presented in this research. A novel reinforcement neural network learning approach based on machine learning is adopted to find th...
In humanitarian aid scenarios, the model of cumulative capacitated vehicle routing problem can be used in vehicle scheduling, aiming at delivering materials to recipients as quickly as possible, thus minimizing their wait time. Traditional approaches...
The Multi-Destination Vehicle Routing Problem (MD-VRP) with a heterogeneous electric fleet is a critical challenge in optimizing commuter services for large-scale institutions and logistics operations. To address the complexities of electric fleet co...
To address the challenges of high energy consumption, substantial carbon emissions, and dynamic customer demand in cold-chain logistics, this paper investigates the balance between sustainable development and operational efficiency for low-carbon dis...
Tower-crane layout planning becomes challenging when deployment decisions are coupled across construction stages. This study develops a dynamic multi-stage mixed-integer linear programming (MILP) model that jointly determines crane type, number, and...
When the quantities of interest remain underdetermined a posteriori, we would like to draw inferences for at least one particular solution. Can we do so in a Bayesian way? What is a probability distribution over an underdetermined quantity? How do we...
Emergency logistics is essential for rapid and efficient disaster response, ensuring the timely availability and deployment of resources to affected areas. In the process of rescue work, the dynamic changes in rescue point information greatly increas...
The parafoil is highly susceptible to deviations from its reference trajectory under wind disturbances. Given its constrained longitudinal control authority, it has limited capability to correct these deviations and regain the intended glide path. To...
This research introduces an innovative strategy to impede and lessen lateral and rear-end vehicular collisions by consolidating braking systems with active emergency steering controls. This study puts forward a T-type active emergency steering method...
Vegetables have a short period of freshness, and therefore, the purchase of vegetables has to be carefully matched with sales, especially in the “small production and big market” setting prevalent in China. Therefore, it is worthwhile to...
Multi-skilled resources have brought more flexibility to resource scheduling and have been a key factor in the research of resource-constrained project scheduling problems. However, existing studies are mainly limited to deterministic problems and ne...
In this paper, a multipopulation dynamic adaptive coevolutionary strategy is proposed for large-scale optimization problems, which can dynamically and adaptively adjust the connection between population particles according to the optimization problem...
The problem of finding the optimal open-loop control for discrete-time stochastic dynamical systems is considered. It is assumed that the initial conditions and external influences are random. The average value of the Bolza functional defined on indi...
A new bio-inspired method for optimizing the objective function on a parallelepiped set of admissible solutions is proposed. It uses a model of the behavior of tomtits during the search for food. This algorithm combines some techniques for finding th...
A novel global harmony search (NGHS) algorithm, as proposed in 2010, is an improved algorithm that combines the harmony search (HS), particle swarm optimization (PSO), and a genetic algorithm (GA). Moreover, the fixed parameter of mutation probabilit...
High-dimensional complex optimization problems are pervasive in engineering and scientific computing, yet conventional algorithms struggle to meet collaborative optimization requirements due to computational complexity. While Chicken Swarm Optimizati...
Freight transportation is becoming an increasingly critical activity for enterprises in a global world. Moreover, the distribution activities have a non-negligible impact on the environment, as well as on the citizens’ welfare. The classical ve...
Deep space missions, and particularly cislunar endeavors, are becoming a major field of interest for the space industry, including for the astrodynamics research community. While near-Earth missions may be completely covered by perturbed Keplerian dy...
Golden jackal optimization (GJO) is an effective metaheuristic algorithm that imitates the cooperative hunting behavior of the golden jackal. However, since the update of the prey’s position often depends on the male golden jackal and there is...
OPTCON is an algorithm for the optimal control of nonlinear stochastic systems which is particularly applicable to economic models. It delivers approximate numerical solutions to optimum control (dynamic optimization) problems with a quadratic object...
We introduce two new search strategies to further improve the performance of vegetation evolution (VEGE) for solving continuous optimization problems. Specifically, the first strategy, named the dynamic maturity strategy, allows individuals with bett...
Background: The dynamic vehicle routing problem (DVRP) is a complex optimization problem that is crucial for applications such as last-mile delivery. Our goal is to develop an application that can make real-time decisions to maximize total performanc...
With the development of electric vehicles, research on the cooperation of transportation networks (TNs) and power distribution networks (PDNs) has become important. Because of practicability, most cooperation research focuses on user equilibrium assi...
This paper comprehensively reviews the spiral dynamics optimization (SDO) algorithm and investigates its characteristics. SDO algorithm is one of the most straightforward physics-based optimization algorithms and is successfully applied in various br...
Decomposition-based many-objective evolutionary algorithms (D-MaOEAs) are brilliant at keeping population diversity for predefined reference vectors or points. However, studies indicate that the performance of an D-MaOEA strongly depends on the simil...
Automatic controls refer to the application of control theory to regulate systems or processes without human intervention, and the notion is often usefully applied to space applications. A key part of controlling flexible space robotics is the contro...
The Dynamic Vehicle Routing Problem (DVRP) is one of the most important problems in the area of enterprise logistics. DVRP problems involve these dynamics: the appearance of customers, travel times, service times, or vehicle availability. One of the...
Surrogate-assisted evolutionary algorithms (SAEAs) are widely used in the field of high-dimensional expensive optimization. However, real-world problems are usually complex and characterized by a variety of features. Therefore, it is very challenging...
We discuss the dynamic mean-variance (MV) problem for pairs trading with the assumptions that one of the security prices satisfies a stochastic volatility model (SVM) and the corresponding price spread follows an Ornstein–Uhlenbeck (OU) process...
The majority of non-linear systems nowadays are controlled online using rapid PI-controllers with linear characteristics. Evolutionary algorithms are rarely used, especially for online adaptive control, due to their time complexity. This paper propos...
In this paper, a novel soft computing technique is designed to analyze the mathematical model of the steady thin film flow of Johnson–Segalman fluid on the surface of an infinitely long vertical cylinder used in the drainage system by using art...
A thermodynamically unstable spin glass growth model described by means of the parametrically-dependent Kardar–Parisi–Zhang equation is analyzed within the symplectic geometry-based gradient–holonomic and optimal control motivated algorithms. The fin...
One fundamental problem of bioinformatics is the computational recognition of DNA and RNA binding sites. Given a set of short DNA or RNA sequences of equal length such as transcription factor binding sites or RNA splice sites, the task is to learn a...
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