To test, compare and improve algorithms and new approaches for staff scheduling, planning problems are needed. Such problems are often not available in literature. Therefore, the Demand Generator was developed to create own problems for staff scheduling. The actual parameters of this tool are based on real data of a call center, which were only slightly modified for the purpose of data protection of the call center. Nevertheless, the tool can also be used for other industries like retail sector or logistics.
The described tool creates for a whole year in hourly resolution values for the staffing demand of a specific workstation or a specific function. Opening hours, holidays, weekdays, min/max staffing levels, stochastic elements, events and weather effects are taken into account by the Demand Generator.
Table of Contents
1 Introduction
1 Function of the Demand Generator
Objectives and Topics
The primary objective of this working paper is to introduce the "Demand Generator," a tool developed to address the lack of realistic staffing demand datasets available for testing and improving algorithms in staff scheduling. It provides a flexible solution that incorporates real-world complexities like opening hours, stochastic elements, events, and weather effects to create volatile demand profiles for various industries.
- Deterministic core modeling for hourly demand.
- Integration of weekday factors to reflect varying demand patterns.
- Implementation of custom events to simulate real-world demand fluctuations.
- Stochastic simulation using the Ornstein-Uhlenbeck process.
- Practical application for personnel scheduling and demand driver derivation.
Excerpt from the Book
1 Introduction
To test, compare and improve algorithms and new approaches for staff scheduling, planning problems are needed. Such problems are often not available in literature. Therefore, the Demand Generator was developed to create own problems for staff scheduling. The actual parameters of this tool are based on real data of a call center, which were only slightly modified for the purpose of data protection of the call center. Nevertheless, the tool can also be used for other industries like retail sector or logistics.
The tool creates for a whole year in hourly resolution values for the staffing demand of a specific workstation or a specific function. Opening hours, holidays, weekdays, min/max staffing levels, stochastic elements, events and weather effects are taken into account by the Demand Generator. Fig. 1 shows an example of the calculated demand for one week.
Summary of Chapters
1 Introduction: This chapter outlines the motivation for creating the Demand Generator, emphasizing its utility for generating realistic test data for staff scheduling algorithms across various industries.
1 Function of the Demand Generator: This chapter provides a detailed technical explanation of how the tool operates, covering the deterministic core, event and weekday factors, stochastic processes, and the final output formats.
Keywords
Demand Generator, Staff Scheduling, Volatile Demand, Ornstein-Uhlenbeck Process, Hourly Resolution, Planning Problems, Deterministic Core, Weekday Factors, Event Simulation, Personnel Planning, Stochastic Modeling, MS Excel, Visual Basic, Call Center, Demand Drivers
Frequently Asked Questions
What is the core purpose of this paper?
The paper introduces a practical software tool, the "Demand Generator," designed to help researchers and practitioners create custom, realistic demand profiles for testing staff scheduling algorithms.
Which industries can use this tool?
While the tool's parameters are derived from call center data, it is designed to be versatile and is applicable to industries like retail or logistics where staffing demand varies hourly.
What is the main goal of the Demand Generator?
The goal is to provide a tool that generates an entire year's worth of staffing demand in hourly resolution, accounting for real-world factors that cause demand volatility.
What scientific methodology is applied for stochastic modeling?
The tool utilizes the Ornstein-Uhlenbeck process, a mathematical model that allows for the simulation of stochastic effects within the demand profiles.
What does the main part of the document describe?
The main part explains the stepwise functioning of the Demand Generator, including how to set deterministic cores, apply weekday/event factors, integrate stochastic processes, and interpret the final output.
Which keywords best characterize this work?
The work is characterized by terms like Staff Scheduling, Volatile Demand, Stochastic Modeling, Demand Generator, and Ornstein-Uhlenbeck Process.
How are "events" integrated into the demand generation?
The user can define specific events (e.g., holidays or promotions) with percentage-based impacts, which are then assigned to specific days of the year to modify the demand profile accordingly.
Can the user define the min/max limits of the generated demand?
Yes, the tool allows users to specify upper and lower bounds to ensure the generated final demand values remain within realistic operational limits for the specific workstation.
How does the tool handle Saturday and Sunday demand?
The generator can model shop or office closures by applying weekday factors to set demand values to zero, or it can generate profiles for the full week depending on user requirements.
What technology was used to build the Demand Generator?
The Demand Generator was developed using MS Excel and Visual Basic (VBA), and the complete source code is provided in the appendix for user transparency and customization.
- Quote paper
- Dr. Maik Günther (Author), 2017, A Generator for Volatile Demand Profiles. A Brief Description of a Tool, Munich, GRIN Verlag, https://www.grin.com/document/373555
