This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. To address the complexity of this NP-hard problem, the HES-IG algorithm combines evolution strategies (ES) and iterated greedy (IG) algorithm, as hybridizing algorithms helps different algorithms mitigate their weaknesses and leverage their respective strengths. The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. Reproduction is carried out using (1 + 5)-ES, generating five offspring from one parent randomly. The selection process employs (µ + λ)-ES, allowing excellent parent solutions to survive multiple generations until a better offspring surpasses them. The IG algorithm’s straightforward search mechanism aids in further improving the solution and avoiding local minima. The destruction operator randomly removes d-jobs, which are then inserted one by one using a construction operator. The local search operator employs a single insertion approach, while the acceptance–rejection criteria are based on a constant temperature. Parameters of both ES and IG algorithms are calibrated using the Multifactor analysis of variance technique. The performance of the HES-IG algorithm is calibrated with other algorithms using the Wilcoxon signed test. The HES-IG algorithm is tested on 21 Nos. Reeves and 30 Nos. Taillard benchmark problems. The HES-IG algorithm has found 15 lower bound values for Reeves benchmark problems. Similarly, the HES-IG algorithm has found 30 lower bound values for the Taillard benchmark problems. Computational results indicate that the HES-IG algorithm outperforms other available techniques in the literature for all problem sizes.

Rapid and precise intervention in disaster and medical-aid scenarios demands aerial platforms that can both survey and physically interact with their environment. This study presents the design, fabrication, modeling, and experimental validation of a one-piece, 3D-printed quadcopter with an integrated six-degree-of-freedom aerial manipulator robotic arm tailored for emergency response. First, we introduce an ‘X’-configured multi-rotor frame printed in PLA+ and optimized via variable infill densities and lattice cutouts to achieve a high strength-to-weight ratio and monolithic structural integrity. The robotic arm, driven by high-torque servos and controlled through an Arduino-Pixhawk interface, enables precise grasping and release of payloads up to 500 g. Next, we derive a comprehensive nonlinear dynamic model and implement an Extended Kalman Filter-based sensor-fusion scheme that merges Inertial Measurement Unit, barometer, magnetometer, and Global Positioning System data to ensure robust state estimation under real-world disturbances. Control algorithms, including PID loops for attitude control and admittance control for compliant arm interaction, were tuned through hardware-in-the-loop simulations. Finally, we conducted a battery of outdoor flight tests across spatially distributed way-points at varying altitudes and times of day, followed by a proof-of-concept medical-kit delivery. The system consistently maintained position accuracy within 0.2 m, achieved stable flight for 15 min under 5 m/s wind gusts, and executed payload pick-and-place with a 98% success rate. Our results demonstrate that integrating a lightweight, monolithic frame with advanced sensor fusion and control enables reliable, mission-capable aerial manipulation. This platform offers a scalable blueprint for next-generation emergency drones, bridging the gap between remote sensing and direct physical intervention.

Airborne wind energy systems (AWES) are able to access stronger and more persistent winds at higher operating altitudes, although system performance strongly depends on the choice of aerodynamic actuation, flight-path geometry, and height of operation under realistic wind conditions. In case of rigid-wing ground-generation (ground‑gen) AWES, the influence of such a combination of operating parameters on traction-phase performance is still inadequately understood at constant settings of the control algorithms and limitations of the hardware. This paper tries to fill this knowledge gap by studying the impact of several key operating parameters of the ground-gen system with the aid of a validated nonlinear kite–tether–winch simulator of the Kitemill KM1 rigid-wing Ground-Gen AWES. Using a one-factor-at-a-time simulation campaign, the influence of fixed flap deflection, lateral path geometry, wind-field formulation, minimum production height, and elevation angle of the helix axis on the reel-out mechanical power and operation margins was examined. Under the formulation of an altitude-dependent wind field with the time-varying ground-reference wind input, the baseline design produces an average reel-out power of 7.56 kW. Application of speed-scheduled flap deflection in the range of conservative values of 0°–10° increases the average reel-out power up to 11.10 kW, which corresponds to an increase of around 47 % while repeated crosswind operation was maintained in the evaluated simulations. Increasing the minimum production height further improves the average reel-out power to 12.96 kW, which is about 71 % above the baseline one. On the other hand, within the tested circle–ellipse comparison, lateral path shape has only a minor influence on average traction power, whereas circular loop radius has a clear effect. Tuning of the elevation angle does not allow increasing the reel-out power further than the minimum height optimization does in the considered operating envelope.