The agricultural equipment market has the characteristics of rapid demand changes and high demand for machine models, etc., so multi-variety, small-batch, and customized production methods have become the mainstream of agricultural machinery enterpri...
In this work, we study the multiresource flexible job-shop scheduling problem (MRFJSSP), which relaxes the standard “simultaneous occupation” policy described in the literature. This policy implies that a job operation starts only when al...
This paper addresses a novel multi-skill resource-constrained project scheduling problem with flexible resource profiles (F-MSRCPSP), in which the resource allocation of each activity consists of a certain number of discrete resources and is allowed...
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...
Addressing the resource constraints, such as manpower and equipment, faced by mine backfilling operations, this study proposed an optimization model for backfill scheduling based on the Resource-Constrained Project Scheduling Problem (RCPSP). The mod...
Real-world projects encounter numerous issues, challenges, and assumptions that lead to changes in scheduling. This exposure has prompted researchers to develop new scheduling models, such as those addressing constrained resources, multi-skill resour...
In engineering R&D organizations, resource contention among autonomous projects creates complex scheduling challenges in distributed multi-project environments. Traditional coordination mechanisms often prioritize global efficiency while overlook...
In multi-project environments characterized by resource constraints and high uncertainty, traditional scheduling approaches often fail to respond effectively to dynamic project conditions. Fixed activity durations and rigid resource allocations limit...
In the era of Industry 5.0, human-centric manufacturing necessitates deep integration between workers and intelligent workshop scheduling systems. However, the inherent variability in worker efficiency due to learning and forgetting effects poses cha...
This paper presents a narrative review on the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) under uncertainty and resource flexibility. Traditional project scheduling assumes complete information and a deterministic environment where...
Efficient scheduling in industrial prefabrication environments—such as Prefabricated Bathroom Unit (PBU) production—faces increasing challenges due to resource limitations, overlapping projects, and complex task dependencies. To address t...
Edge computing networks represent an emerging technological paradigm that enhances real-time responsiveness for mobile devices by reallocating computational resources from central servers to the network’s edge. This shift enables more efficient...
Container-based cloud platforms enable flexible and lightweight application deployment, yet container scheduling remains challenged by resource fragmentation, load imbalance, excessive energy consumption, and service-level agreement (SLA) violations....
Compared with the traditional collocated multi-input multi-output system (C-MIMO), distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage, making them strong candidates for next-generation communication architecture. A...
In this paper, a real-time scheduling problem of a dual-resource flexible job shop with robots is studied. Multiple independent robots and their supervised machine sets form their own work cells. First, a mixed integer programming model is establishe...
Multi-FPGA systems can form larger and more powerful computing units through high-speed interconnects between chips, and are beginning to be widely used by various computing service providers, especially in edge computing. However, the new computing...
The rapidly evolving business landscape, driven by stringent energy conservation policies, compels construction firms to adopt energy-efficient project-centric structures, particularly in modern construction projects. These firms face a complex, mult...
In situations where an organization has limited human resources and a lack of multi-skilled employees, organizations pay more and more attention to cost control and personnel arrangements. Based on the consideration of the service personnel schedulin...
To improve the service quality of cloud computing, and aiming at the characteristics of resource scheduling optimization problems, this paper proposes a hybrid multi-objective bat algorithm. To prevent the algorithm from falling into a local minimum,...
This study addresses the Multi-Skill Resource-Constrained Project Scheduling Problem (MSRCPSP) by investigating the simultaneous effects of workforce skill proficiency (depth) and skill versatility (breadth) on project makespan reduction. Two state-o...
This study developed an optimization model for the strategic location of maintenance resource supply sites and the scheduling of multiple resources following failures in urban metro systems, with the objective of enhancing system resilience. The mode...
To address the time–cost trade-off challenge in real-world practices, a bi-objective optimization model of the Multi-mode Resource-Constrained Project Scheduling Problem is proposed with simultaneously minimizing both the project makespan and t...
Space–Air–Ground–Sea Integrated Networks (SAGSINs) are emerging as a key enabling architecture for broadband maritime connectivity, where heterogeneous access tiers (shore, aerial, and satellite) jointly support delay-sensitive and...
In this study, the multi-mode resource-constrained multi-project scheduling problems (MMRCMPSPs) considering supply management and sustainable approach in the construction industry under uncertain conditions have been investigated using evidence theo...
The characteristics of railway dangerous goods accidents are very complex. The rescue of railway dangerous goods accidents should consider the timeliness of rescue, the uncertainty of traffic environment and the diversity of rescue resources. Thus, t...
Directional unmanned aerial vehicle (UAV) ad hoc networks (DUANETs) are widely applied due to their high flexibility, strong anti-interference capability, and high transmission rates. However, within directional networks, complex mutual interference...
Effective resource management constitutes a cornerstone of construction project success. This is a challenging combinatorial optimization problem with multiple and contradictory objectives whose complexity rises disproportionally with the project siz...
Aiming to mitigate renewable energy curtailment and curb the carbon emissions of traditional thermal power units (TPUs), this paper proposes a stochastic optimal scheduling of a multi-energy complementary base considering multi-resource reserve and T...
Complex water networks face prominent contradictions among flood control, water supply, and ecological protection, and traditional scheduling models struggle to address multi-dimensional water security challenges. To solve this problem, this study pr...
In the era of aiming toward reaching a sustainable ecosystem, the primary focus is to curb the emissions generated by non-conventional resources. One way to achieve this goal is to find an alternative to traditional power plants (TPP) by integrating...
Efficient resource allocation and task scheduling remain fundamental challenges in cloud computing because of resource heterogeneity, dynamic workload characteristics, and the increasing demand for scalable, energy-efficient, and sustainable cloud in...
To address the strong constraints, multiple objectives, and high dynamism of space telemetry, tracking, and command (TT&C) resource scheduling in flight-type launch scenarios, this study proposes a dynamic scheduling approach that integrates prio...
Heterogeneous architecture-based systems-on-chip enable the development of flexible and powerful multifunctional RF systems. In complex and dynamic environments where applications arrive continuously and stochastically, real-time scheduling of multip...
Addressing the high-dimensional, strongly constrained multi-objective optimization problem of air–ground collaborative jamming scheduling in complex terrain, existing methods are often limited by incomplete modeling and low optimization efficie...
Inverse synthetic-aperture radar (ISAR) can achieve precise imaging of targets, which enables precise perception of battlefield information, and it has become one of the most important tasks for radar systems. In multi-target scenarios, a resource sc...
In this journal, we proposed a novel method of using multi-task learning to switch the scheduling algorithm. With multi-task learning to change the scheduling algorithm inside the scheduling framework, the scheduling framework can create a scheduler...
In this paper, we tackle the challenge of optimizing resource utilization and demand-driven allocation in dynamic, multi-dimensional heterogeneous environments. Traditional containerized task scheduling systems, like Kubernetes, typically rely on def...
Cloud computing has transformed the delivery of modern applications and services by providing scalable, flexible, and cost-effective access to computing resources. One of the most critical challenges in cloud environments is the efficient distributio...
Inverse synthetic aperture radar (ISAR) three-dimensional (3D) imaging technology enables the acquisition of clear 3D structures of targets, significantly enhancing target recognition performance. In resource-constrained environments, an effective re...
With the emergence of vehicular edge computing (VEC) and electric vehicles (EVs), integrating computation and charging tasks presents challenges due to limited resources and dynamic vehicular networks. This research focuses on the joint optimization...
IoT embedded systems have multiple objectives that need to be maximized simultaneously. These objectives conflict with each other due to limited resources and tradeoffs that need to be made. This requires multi-objective optimization (MOO) and multip...
This study addresses continuous UAV patrol scheduling for forest fire prevention in the Greater Khingan Mountains under multiple airports, UAV types, and monitoring zones. A multi-objective scheduling model is established considering UAV availability...
Multi-Agent Systems (MAS) have been seen as an attractive area of research for civil engineering professionals to subdivide complex issues. Based on the assignment’s history, nearby agents, and objective, the agent intended to take the appropri...
To address the challenges posed by the instability of renewable energy output and load fluctuations on grid operations and to support the low-carbon sustainable development of the energy system, this paper integrates artificial intelligence technolog...
In response to the increasing operational complexity of inland waterway systems, this study develops a multi-objective optimization framework for ship lock scheduling under energy-consumption and resource constraints. The model evaluates five operati...
The widely recognized measure for resources called resource strength (RS) does not fully capture the resources complexity of a project. Therefore, it cannot be used as a standalone measure to distinguish the complexity of various instances of project...
This research introduces a stochastic version of the multi-mode resource-constrained project scheduling problem (MRCPSP) and its mathematical model. In addition, an efficient multi-start iterated local search (MS-ILS) algorithm, capable of solving th...
An energy hub (EH) provides an effective solution to the management of local integrated energy systems (IES), supporting the optimal dispatch and mutual conversion of distributed energy resources (DER) in multi-energy forms. However, the intrinsic st...
Synthetic Aperture Radar (SAR) image interpretation in dynamic scenarios faces critical challenges, including sluggish multi-agent scheduling responses, sub-optimal task-resource matching, and low full-pipeline collaborative efficiency. To address th...
The increasing penetration rate of distributed resources in the distribution network has brought about significant volatility and uncertainty problems. Demand response (DR) can flexibly change the energy consumption method of the user to balance supp...
of 20