Coverage Path Planning (CPP) for fixed-wing aerial robots remains challenging in dynamic and partially unknown environments due to the need to simultaneously satisfy coverage completeness, kinematic feasibility, and real-time adaptability. Convention...
Aiming at the problem that the Osprey Optimization Algorithm (OOA) does not have high optimization accuracy and is prone to falling into local optimum, an Improved Osprey Optimization Algorithm Based on a Two-Color Complementary Mechanism for Global...
In the operational, strategic and tactical decision-making problems of the agri-food supply chain, the perishable nature of the commodities can represent a particular complexity problem. It is, therefore, appropriate to consider decision support tool...
The expansion of the tourism industry has led to the development of various methods to find optimal tourism paths. However, planning tourism paths in hilly areas remains complex and has specific challenges. Different algorithms have been used to plan...
This paper presents an innovative approach using Dynamical Systems Theory (DST) for interplanetary orbit insertion into Saturn−Titan three−body orbits. By leveraging DST, this study identifies invariant manifolds guiding a spacecraft into...
This study investigates the optimization of thickness distribution in simply supported and cantilever plates to maximize gaps between adjacent natural frequencies. The research employs a genetic algorithm (GA) as the primary optimization tool, with t...
In the industrial sector, production processes are continuously evolving, but issues and delays in production are still commonplace. Complex problems often require input from production managers or experts even though Industry 4.0 provides advanced t...
Combined heat and power economic dispatch (CHPED) is a challenging nonlinear, nonconvex optimization problem characterized by the simultaneous coordination of electrical and thermal power generation under complex operational constraints. The presence...
Many kinds of panel structures are proposed in aircraft design. This study presents a topology optimization method to improve the buckling resistance of panel structures. It should be noted that a popular configuration of the present panel structure...
This study aims to develop a high-precision and efficient body-fitted mesh framework for fluid topology optimization, focusing on minimizing flow resistance in incompressible steady Newtonian fluid systems. Different from traditional fixed-mesh metho...
In the noisy medium-scale quantum era, quantum computers are constrained by a limited number of qubits, restricted physical topological structures, and interference from environmental noise, making efficient and stable circuit scheduling a significan...
Hierarchical decision-making processes traditionally modeled as bilevel optimization problems are widespread in modern engineering and social systems. In this work, we deal with a leader with a population of followers in a hierarchical order of play....
In the dynamic vehicle routing problem with mixed backhauls (DVRPMB) both pick up orders and delivery orders, not related to each other, are served. The requests of the former arrive dynamically while the latter are known a priori. In this study, we...
This paper considers a class of distributed online aggregative optimization problems over an undirected and connected network. It takes into account an unknown dynamic environment and some aggregation functions, which is different from the problem fo...
A pseudo-spectral control algorithm based on adaptive Gauss collocation point reconstruction is proposed to efficiently solve the optimal dynamics control problem of industrial robots. A mathematical model for the kinematic relationship and dynamic o...
An aging society increases the demand for emergency services, such as EMS. The more often EMS is needed by patients, the more medical staff are needed. During the COVID-19 pandemic, the lack of medical staff became a critical issue. This research aim...
The major function of dynamic networks is to sense information from the environment and process the information to the downstream. Therefore how to measure the information transmission ability of a dynamic network is an important topic to evaluate ne...
Bolstered by emerging sixth-generation (6G) communication technology, space–air–ground– sea integrated networks (SAGSINs) are reshaping edge computing through the synergistic use of space, aerial, terrestrial, and maritime platforms...
As industrial practices continue to evolve, complex process industries often exhibit characteristics such as multivariate correlation, dynamism, and nonlinearity, making traditional mechanism modeling inadequate in terms of addressing the intricacies...
The main concern of the paper is the concurrent treatment of size and layout variables in the static–dynamic coupled layout optimization of stiffened plates. As compared to size optimization alone, layout optimization is a more challenging task...
Dynamic multi-objective optimization problems (DMOPs) are optimization problems where elements of the problems, such as the objective functions and/or constraints, change with time. These problems are characterized by two or more objective functions,...
Nowadays, multi-access edge computing (MEC) has been widely recognized as a promising technology that can support a wide range of new applications for the Internet of Things (IoT). In dynamic MEC networks, the heterogeneous computation capacities of...
Real-world production scheduling scenarios are often not discrete, separable, iterative tasks but rather dynamic processes where both external (e.g., new orders, delivery shortages) and internal (e.g., machine breakdown, timing uncertainties, human i...
In this paper, we consider a problem of the dynamic pricing and inventory control for non-instantaneous deteriorating items with uncertain demand, in which the demand is price-sensitive and governed by a diffusion process. Shortages and remains are p...
Dynamic multi-objective optimization problems (DMOPs) have become a research hotspot in engineering optimization, because their objective functions, constraints, or parameters may change over time, while quickly and accurately tracking the changing P...
Decomposition-based multi-objective evolutionary algorithms provide a good framework for static multi-objective optimization. Nevertheless, there are few studies on their use in dynamic optimization. To solve dynamic multi-objective optimization prob...
This paper introduces an innovative approach to explore the capabilities of Quantum Annealing (QA) for trajectory optimization in dynamic systems. The proposed method involves transforming trajectory optimization problems into equivalent binary optim...
Regarding the discretization issue in the process of a simultaneous approach for dynamic optimization problems, a configuration strategy based on the density function has been proposed for the finite element distribution of dynamic optimization probl...
Perishable goods have a limited shelf life, and inventory should be discarded once it exceeds its shelf life. Finding optimal inventory management policies is essential since inefficient policies can lead to increased waste and higher costs. While ma...
We consider an optimal control problem with the discounted and average payoff. The reward rate (or cost rate) can be unbounded from above and below, and a Markovian switching stochastic differential equation gives the state variable dynamic. Markovia...
This paper presents an approach to managing the thermal power plant’s flexible operation based on the steam generation process optimization. A strategy at the process level, as a first step in the operational optimization of the entire power pl...
This paper is concerned to the fire localization problem for large-space buildings. Two kinds of circular fire source arrangement localization methods are proposed on the basis of the dynamic optimization technology. In the Range-Point-Range frame, a...
To address the issue that the performance-index function encompassing both dynamic and control processes in traditional adaptive dynamic programming (ADP) cannot be optimized as time approaches infinity, this paper proposes an optimal tracking contro...
This paper introduces GEKKO as an optimization suite for Python. GEKKO specializes in dynamic optimization problems for mixed-integer, nonlinear, and differential algebraic equations (DAE) problems. By blending the approaches of typical algebraic mod...
In a human-robot collaborative disassembly line, multiple people and robots collaboratively perform disassembly operations at each workstation. Due to dynamic factors, such as end-of-life product quality and human capabilities, the line balancing pro...
This paper revisits the dynamic MV portfolio selection problem with cone constraints in continuous-time. We first reformulate our constrained MV portfolio selection model into a special constrained LQ optimal control model and develop the optimal por...
We present the open-source software framework in JModelica.org for numerically solving large-scale dynamic optimization problems. The framework solves problems whose dynamic systems are described in Modelica, an open modeling language supported by se...
To improve the speed and dynamic adaptability of robotic arm trajectory planning, a collision-free optimal trajectory planning method combining non-uniform adaptive time meshing and bounding box collision detection was proposed. First, the dynamics a...
This paper identifies four common misconceptions about the scalability of volunteer computing on big data problems. The misconceptions are then clarified by analyzing the relationship between scalability and the impact factors including the problem s...
In a resource-constrained project scheduling problem, most studies ignore that resource supply is a separate optimization problem, which is not in line with the actual situation. In this study, the project scheduling problem and the resource supply p...
Urban logistics consumes a large portion of energy resources worldwide. Thus, optimization algorithms are used to define mobility modes, vehicle fleets, routing plans, and last-mile delivery operations to reduce energy consumption such as metaheurist...
With the growing popularity of autonomous electric vehicles (AEVs), optimizing their path-planning and charging strategy has become a critical research area. However, the dynamic nature of transport networks presents a significant challenge when ensu...
Unmanned-aerial-vehicle (UAV)-aided data collection for Internet of Things applications has attracted increasing attention. This paper investigates motion planning for UAV collecting low-power ground sensor node (SN) data in a dynamic jamming environ...
Recognizing the importance of incorporating different risk measures in the portfolio management model, this paper examines the dynamic mean-risk portfolio optimization problem using both variance and value at risk (VaR) as risk measures. By employing...
To strengthen the population diversity and search capability of equilibrium optimizer (EO), a dynamic multi-population mutation architecture-based equilibrium optimizer (DMMAEO) is proposed. Firstly, a dynamic multi-population guidance mechanism is c...
Population-based metaheuristics can be seen as a set of agents that smartly explore the space of solutions of a given optimization problem. These agents are commonly governed by movement operators that decide how the exploration is driven. Although m...
Node placement is one of the basic problems in a Wireless Sensor Network (WSN). During the operation of a WSN, sensor nodes may fail or die suddenly, which may lead to a coverage hole. To solve this problem, the node placement needs to be re-optimize...
This paper studies an averaged Linear Quadratic Regulator (LQR) problem for a parabolic partial differential equation (PDE), where the system dynamics are affected by uncertain parameters. Instead of assuming a deterministic operator, we model the un...
Optimal tracking control aims to steer a dynamical system along a desired reference trajectory while minimizing a prescribed performance cost. This problem becomes substantially more difficult when both the controlled system dynamics and the target d...
Intelligent weather route optimization method was an essential guarantee for safe and efficient navigation of ships. In traditional methods, the multi-stage decision-making method was generally used to solve route dynamic optimization problems, in wh...
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