A framework for simulation-based optimization of business process models

Abstract

The Assignment Problem is a classical problem in the field of combinatorial optimization, having a wide range of applications in a variety of contexts. In general terms, the Assignment Problem consists of determining the best assignment of tasks to agents according to a predefined objective function. Different variants of the Assignment Problem have been extensively investigated in the literature in the last 50 years. In this work, we introduce and analyze the problem of optimizing a business process model with the objective of finding the most beneficial assignment of tasks to agents. Despite similarities, this problem is distinguished from the traditional Assignment Problem in that we consider tasks to be part of a business process model, being interconnected according to defined rules and constraints. In other words, assigning a business process to agents is a more complex form of the Assignment Problem. Two main categories of business processes, assignment-independent and assignment-dependent, are distinguished. In the first category, different assignments of tasks to agents do not affect the flow of the business process, while processes in the second category contain critical tasks that may change the workflow, depending on who performs them. In each category several types of processes are studied. Algorithms for finding optimal and near-optimal solutions to these categories are presented. For the first category, depending on the type of process, the Hungarian algorithm is combined with either the analytical method or simulation to provide an optimal solution. For the second category, we introduce two algorithms. The first one finds an optimal solution, but is feasible only when the number of critical tasks is small. The second algorithm is applicable to large number of critical tasks, but provides a near-optimal solution. In the second algorithm a hill-climbing heuristic method is combined with the Hungarian algorithm and simulation to find an overall near-optimal solution. A series of tests is conducted which demonstrates that the proposed algorithms efficiently find optimal solutions for assignment-independent and near-optimal solutions for assignment-dependent processes.

Automatic Resource Allocation in Business Processes: A Systematic Literature Survey

“…Ten studies consider attributes belonging to the expertise category [2,15,28,32,38,42,47,63,68,69]. We found that amount [16,51,60,61] and social context [34,36,47,69] are considered less often (4 studies each).…”

“…Traditionally, resource allocation is a manual effort in an organization where a human being assigns tasks to qualified resources (push principle), or the staff members select tasks on their own from a task list (pull principle) [46]. In operations management, the problem of allocating a resource to tasks has a very long tradition and is known as the Assignment Problem; it has been discussed in different versions [32].…”

“…While some studies create advanced queue models (3 studies) [21,27,65] as basis of their resource allocation approach, Hirsch et al [24] simply use the constraints between the activities defined in the process model. As direct input (12 studies), traditional process models are used to create heuristics (5 studies) [9,16,32,45,70] for the resource allocation, or for genetic or machine learning (ML) algorithms (3 studies) [28,51,60]. We discuss the concrete solution techniques in Section 5.4 in detail.…”

“…The variety of approaches support different optimization goals, such as minimizing the cycle time or process cost, balancing the resources' workload, or finding the best-fitting resource. Most approaches support 1-to-1 allocations (i.e., one resource to one task), e.g., [3,24,27,32].…”

An Innovative Model for Measuring Attitudes towards Digital Technology Platforms

“…This is because it enables the design of an organisational architecture as well as specific solutions and processes used and taking place within the organisation (Wynn and Clarkson, 2018). These include those that involve undertaking and intensifying cooperation between enterprises in order to combine various business models (Wikström, Artto, Kujala and Söderlund, 2010), solving various management-related and organisational problems (Szarucki, 2013), simulating activities and directions of development that are desired in the organisation in specific circumstances or market situations (Levinthal and Marengo, 2016), optimising the functioning of enterprises (Kamrani, Ayani and Moradi, 2011) or effective risk management (Bac, 2010). For this reason, models are used on a large scale in the practice of business operations.…”