Business Process Instances Scheduling with Human Resources Based on Event Priority Determination

Abstract

Business Process Management (BPM) is concerned with continuously enhancing business processes. However, this cannot be achieved without an effective Resource allocation and a priority-based scheduling. These are important steps towards time, cost and performance optimization in business processes. Even though there are several approaches and algorithms for scheduling and resource allocation problems, they do not take into consideration information gathered from past process executions, given the stateless aspect of business processes. Extracting useful knowledge from this information can help achieving an effective instance scheduling decisions without compromising cost or quality of service. In this paper, we pave the way for a combination approach which is based on unsupervised machine learning algorithms for clustering and genetic algorithm (GA) to ensure the assignment of the most critical business process instance tasks, to the qualified human resource while respecting several constraints such as resource availability and reliability, and taking into consideration the priority of the events that launch the process instances. A case study is presented and the obtained results from our experimentations demonstrate the benefit of our approach and allowed us to confirm the efficiency of our assumptions.

Towards Smart Incident Management Under Human Resource Constraints for an IoT-BPM Hybrid Architecture

“…Another challenge is event/incident management and scheduling in business processes. In fact, business process instances are launched by events, and an effective management of those event and the determination of their priority ensure a positive impact on business process performance by achieving an efficient time, cost and resource management [22]. However, with the emergence of IoT those challenges (data and events management) have become more complex since we are dealing now with a bidirectional communication loop between business process layer and IoT layer: the IoT components and devices generate data and produce events by interacting with their physical environment and those events launch several business process instances (bottom-up) and business process instances execution can also generate data as an output and ensure en IoT event management (top-down).…”

“…The case study of our research work belongs to silver economy domain [23] which is a new industrial sector officially launched in 2013 in France, in order to create personalized services and new technologies that are expected to improve disability free life expectancy or to help dependent elderly people and their caregivers on a day-to-day basis [22]. Most countries all over the world live the demographic transition of aging population.…”

“…In the next section, we present our IoT-BPM integration approach for smart incident/event management in IoT-based business processes, under human resource constraints. [22] 4 Proposed Approach We propose in this paper an approach for incident Management (see fig. 4) that ensures a beneficial IoT and BPM communication for achieving a smart IoT event management and also a flexible business process instances scheduling under human resource constraints.…”

“…To tackle this optimization problem linked to human resource allocation, we propose a matching step using genetic algorithm to ensure an efficient matching between the IoT event (that will launch a business process instance) and the most suitable and available human resources. Genetic algorithm is a meta-heuristic that has been proposed in 1975 by John Holland, it belongs to evolutionary algorithms group [29] and it aims to solve optimization problems by simulating the intelligence of natural selection and genetics following specific phases [22]:…”

Priority-Based Event Management using Fuzzy Logic for an IoT-BPM Architecture

“…Business process instances scheduling and event management are considered as a crucial step in the journey of business process performance improvement. Several research contributions in the literature focus on scheduling business process instances, and optimizing resource allocation based on different methodologies and different algorithms such as [1] [2] [3] [4] [5] just to name a few. However, the new digitized era and the rise of several new technologies especially Internet of Things (IoT) implies new business process scheduling problems and challenges linked basically to limited resources or the need to use those resources (especially in case of human resources) in an optimal and flexible way by achieving priority-based scheduling.…”