Differential evolution (DE) is one of the best evolutionary algorithms (EAs). The effort improving its performance has received great research attentions, such as adaptive DE (JADE). Based on analysis aspects that may improve JADE, we introduce a modified JADE version with sorting crossover rate (CR). In CR values are generated based mean value and Gaussian distribution. proposed algorithm, smaller assigned to individual better fitness value. Therefore, components individuals, which have...

Effective sales prediction for e-commerce would assist retailers in developing accurate production and inventory control plans, which further help them to reduce costs overdue losses. This paper develops a systematic method prediction, with particular focus on predicting the of products short shelf lives. The short-shelf-life product problem is poorly addressed existing literature. Unlike long lives, such as fresh milk exhibit significant fluctuations volume incur high costs. Therefore,...

Reducing carbon emissions is becoming increasingly important in manufacturing, highlighting the need for green scheduling flexible systems. In real-world jobs often require transportation between machines, making resources essential effective and system optimization. This paper addresses job shop problem Automated Guided Vehicles (AGV) (EVFJSP-AGV), improving coordination machine operations AGV allocation to minimize makespan, energy consumption, distance. Detailed consumption models both...

The optimal power flow problem is one of the most widely used problems in system optimizations, which are multi-modal, non-linear, and constrained optimization problems. Effective methods can be considered tackling In this paper, an ϵ-constrained method-based adaptive differential evolution proposed to solve method improved tackle constraints, a p-best selection based on constraint violation implemented evolution. single multi-objective IEEE 30-bus test verify effectiveness εadaptive...

The implementation of the autonomous unmanned aerial mobility is a game changer for on-demand delivery service in crowded urban setting. In this study, first its kind commercial vehicle (UAV) program China targeted. Different from traditional ground pickup and services, mode considers not only time window constraints, but also spatial conflicts incurred during take-off landing operations UAVs. To obtain optimal flying routes focused problem, mixed integer programming model formulated. Due to...

Vehicle routing problems (VRPs) are challenging problems. Many variants of the VRP have been proposed. However, few studies on combined robustness and just-in-time (JIT) requirements with uncertainty. To solve problem, this paper proposes just-in-time-based robust multiobjective vehicle problem time windows (JIT-RMOVRPTW) for assembly workshop. Based conflict between uncertain JIT requirements, a strategy was measure solution, metric designed as objective. Afterwards, two-stage nondominated...

In the modern age of Industry 4.0 and manufacturing servitisation, energy saving environment consciousness are regarded as vital themes in processes to reduce carbon tax achieve sustainable development. For past 20 years, concept green has grown from infancy a fully formed framework agreed upon by world-leading enterprises. With unprecedented development information technology today, industrial data collected could assist in-depth study on manufacturing, which ranges operations machining...

This paper proposes an effective Memetic Algorithm (MA) for the Flexible Job Shop Scheduling Problem (FJSP) with objective of minimising makespan. The proposed MA is a combination TABU Search (TS) and Genetic (GA). hybridisation presents way performing both exploration exploitation by incorporating local search abilities TS global reaching capabilities GA. approach provides encoding method, genetic operators neighbourhood structure in order to effectively solve FJSP. To evaluate performance...

The article puts forward the new layout methodology of multi-floor linear cellular manufacturing layout. proposed equipment not just breaks conventional single-floor but also meets requirements intelligent workshop for stereoscopic aisle cell. takes into account least space occupation as well shortest total distance logistics objective function, besides considering limitations that exist between equipment, different planes, levels, and so on; also, a mathematical model is put forward. solved...

In recent years, the rapid development of artificial intelligence and data science has given rise to study driven algorithms in highly volatile systems. The scheduling complex shop floor resources falls into such a category, which is often non-linear nature, time varying, multi-objective, subject interruptions. Ergo, machine learning-based scheduling, become research hotspot attracted attention many scholars. literature, methods employed solving problems are based on various perspectives, as...

In a typical discrete manufacturing process, new type of reconfigurable production line is introduced, which aims to help small- and mid-size enterprises improve machine utilization reduce cost. order effectively handle the scheduling problem for system, an improved multi-objective particle swarm optimization algorithm based on Brownian motion (MOPSO-BM) proposed. Since existing MOPSO algorithms are easily stuck in local optimum, global search ability proposed method enhanced random...

Surrogate models are commonly used to approximate the multivariate input or output behavior of complex systems. In this paper, surrogate assisted calibration frameworks proposed calibrate crowd model. To integrate into evolutionary framework, both offline and online training based approaches developed. The needs generate set in advance, while can adaptively build re-build model along process. Our simulation results demonstrate that framework with is effective using artificial neural network...