Biomimetic optimization transfers biological information-processing mechanisms into computational systems. Ant colony optimization (ACO) is a canonical example: artificial ants functionally abstract pheromone-mediated stigmergy, decentralized explora...
We examine how site-based path planning algorithms for enclosed spaces can be enhanced with situational detail. Addressing this question has led to value propositions in facility design, where there is often a call to match, map, and merge infrastruc...
Urban logistics face complexity due to traffic congestion, fleet heterogeneity, warehouse constraints, and driver workload balancing, especially in the Heterogeneous Multi-Trip Vehicle Routing Problem with Time Windows and Time-Varying Networks (HMTV...
Cervical cancer is the fourth most commonly diagnosed cancer and one of the leading causes of cancer-related deaths among females worldwide. Early diagnosis can greatly increase the cure rate for cervical cancer. However, due to the need for substant...
Energy efficiency and spectrum efficiency are the most important issues for future mobile systems. Heterogeneous networks (HetNets) with coordinated multiple points (CoMP) are wildly approved as a promising solution to meet increasing demands of mobi...
Considering the requirements of the actual production scheduling process, the utilization of the genetic programming hyper-heuristic (GPHH) approach to automatically design dispatching rules (DRs) has recently emerged as a popular optimization approa...
11 March 2023
Providing the right products, at the right place and time, according to their customer’s preferences, is a problem-seeking solution, especially for companies operating in the retail industry. This study presents an integrated product RS that co...
A multi-objective evolutionary algorithm based on decomposition (MOEA/D) serves as a robust framework for addressing multi-objective optimization problems (MOPs). However, it is widely recognized that the applicability of a fixed offspring-generating...
Solving of combinatorial optimization problems is a common practice in real-life engineering applications. Trusses, cranes, and composite laminated structures are some good examples that fall under this category of optimization problems. Those exampl...
In this paper, a new hybrid prediction method is proposed for estimating remaining useful life, emissions, and performance parameters using experimental data obtained from a micro-turbojet engine. Experiments were conducted under various rotational s...
Disease phenotypes are generally caused by the failure of gene modules which often have similar biological roles. Through the study of biological networks, it is possible to identify the intrinsic structure of molecular interactions in order to ident...
Urban battery swapping station (BSS) planning is difficult because site opening, service-module allocation, user assignment, battery degradation pressure, travel burden, and congestion are tightly coupled. A plan that minimizes investment alone may c...
Real-time order arrivals and stringent timeliness demands in e-commerce pose significant challenges to production-distribution coordinated scheduling in distributed manufacturing systems. This paper tackles the integrated production and distribution...
Variational auto-encoders (VAE) have recently been successfully applied in the intelligent fault diagnosis of rolling bearings due to its self-learning ability and robustness. However, the hyper-parameters of VAEs depend, to a significant extent, on...
In this study, we allocated soft open points (SOPs) and distributed generation (DG) units simultaneously with and without network reconfiguration (NR), and investigate the contribution of SOP losses to the total active losses, as well as the effect o...
Data from omics studies have been used for prediction and classification of various diseases in biomedical and bioinformatics research. In recent years, Machine Learning (ML) algorithms have been used in many different fields related to healthcare sy...
Electrical load forecasting provides knowledge about future consumption and generation of electricity. There is a high level of fluctuation behavior between energy generation and consumption. Sometimes, the energy demand of the consumer becomes highe...
The interpretation of Myocardial Infarction (MI) via electrocardiogram (ECG) signal is a challenging task. ECG signals’ morphological view show significant variation in different patients under different physical conditions. Several learning al...
This paper addresses a human resource allocation problem with spatial-temporal constraints (HRAP-SC) in the parallel assembly of complex products, such as satellites and aircraft. It involves coordinating a limited pool of multi-skilled workers acros...
Learning-based hyper-heuristics for combinatorial optimization select from among low-level operators or tune the parameters of a single metaheuristic. However, online selection among complete population-based metaheuristics that share one evolving po...
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