相关论文: An Optimization Framework for a Dynamic Multi-Skil…

We consider the Windows Scheduling problem. The problem is a restricted version of Unit-Fractions Bin Packing, and it is also called Inventory Replenishment in the context of Supply Chain. In brief, the problem is to schedule the use of…

This paper introduces a new generic problem to the literature of Workforce Scheduling and Routing Problem. In this problem, multiple workers are assigned to a shared vehicle based on their qualifications and customer demands, and then the…

This paper investigates the optimization problem of scheduling autonomous mobile robots (AMRs) in hospital settings, considering dynamic requests with different priorities. The primary objective is to minimize the daily service cost by…

In a data stream management system (DSMS), users register continuous queries, and receive result updates as data arrive and expire. We focus on applications with real-time constraints, in which the user must receive each result update…

Due to the limited resource capacity of edge servers and the high purchase costs of edge resources, service providers are facing the new challenge of how to take full advantage of the constrained edge resources for Internet of Things (IoT)…

In services such as retail audits and urban infrastructure monitoring, a platform dispatches rewarded, location-based micro-tasks to mobile workers traveling along personal origin-destination (OD) trips under hard time budgets. As requests…

Multi-user delay constrained scheduling is important in many real-world applications including wireless communication, live streaming, and cloud computing. Yet, it poses a critical challenge since the scheduler needs to make real-time…

Modern business models have enabled service systems to leverage a large pool of casual employees with flexible hours, paid based on piece rates, to fulfill on-demand work. These systems have been successfully implemented in sectors such as…

With the development of e-commerce during the Covid-19 pandemic, one of the major challenges for many parcel logistics companies is to design reliable and flexible scheduling algorithms to meet uncertainties of parcel arrivals as well as…

This paper develops an inherently parallelised, fast, approximate learning-based solution to the generic class of Capacitated Vehicle Routing Problems with Time Windows and Dynamic Routing (CVRP-TWDR). Considering vehicles in a fleet as…

The digital transformation is pushing the existing network technologies towards new horizons, enabling new applications (e.g., vehicular networks). As a result, the networking community has seen a noticeable increase in the requirements of…

We consider a vehicle routing problem which seeks to minimize cost subject to time window and synchronization constraints. In this problem, the fleet of vehicles is categorized into regular and special vehicles. Some customers require both…

We propose a manager-worker framework based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), \ie~multiple-vehicle TSP with time window and rejections (mTSPTWR), where customers who…

Bus timetable optimization is a key issue to reduce operational cost of bus companies and improve the service quality. Existing methods use exact or heuristic algorithms to optimize the timetable in an offline manner. In practice, the…

This paper addresses the critical challenge of managing Quality of Service (QoS) in cloud services, focusing on the nuances of individual tenant expectations and varying Service Level Indicators (SLIs). It introduces a novel approach…

MapReduce has become a popular programming model for running data intensive applications on the cloud. Completion time goals or deadlines of MapReduce jobs set by users are becoming crucial in existing cloud-based data processing…

With the rapid advancement of mobile networks and the widespread use of mobile devices, spatial crowdsourcing, which involves assigning location-based tasks to mobile workers, has gained significant attention. However, most existing…

In task allocation for real-time domains, such as disaster response, a limited number of agents is deployed across a large area to carry out numerous tasks, each with its prerequisites, profit, time window and workload. To maximize profits…

Scheduling is a fundamental task occurring in various automated systems applications, e.g., optimal schedules for machines on a job shop allow for a reduction of production costs and waste. Nevertheless, finding such schedules is often…

In data-intensive applications data transfer is a primary cause of job execution delay. Data access time depends on bandwidth. The major bottleneck to supporting fast data access in Grids is the high latencies of Wide Area Networks and…