A network model for the rotating workforce scheduling problem

Networks ◽  
1990 ◽  
Vol 20 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Nagraj Balakrishnan ◽  
Richard T. Wong
Keyword(s):  
Network Model ◽  
Scheduling Problem ◽  
Workforce Scheduling

scholarly journals Workforce Scheduling with Order-Picking Assignments in Distribution Facilities

2021 ◽  
Author(s):  
Arpan Rijal ◽  
Marco Bijvank ◽  
Asvin Goel ◽  
René de Koster
Keyword(s):  
Time Windows ◽  
Real Life ◽  
Labor Cost ◽  
Order Picking ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Workforce Scheduling ◽  
Solution Approach ◽  
Business Application ◽  
End Times

Scheduling the availability of order pickers is crucial for effective operations in a distribution facility with manual order pickers. When order-picking activities can only be performed in specific time windows, it is essential to jointly solve the order picker shift scheduling problem and the order picker planning problem of assigning and sequencing individual orders to order pickers. This requires decisions regarding the number of order pickers to schedule, shift start and end times, break times, as well as the assignment and timing of order-picking activities. We call this the order picker scheduling problem and present two formulations. A branch-and-price algorithm and a metaheuristic are developed to solve the problem. Numerical experiments illustrate that the metaheuristic finds near-optimal solutions at 80% shorter computation times. A case study at the largest supermarket chain in The Netherlands shows the applicability of the solution approach in a real-life business application. In particular, different shift structures are analyzed, and it is concluded that the retailer can increase the minimum compensated duration for employed workers from six hours to seven or eight hours while reducing the average labor cost with up to 5% savings when a 15-minute flexibility is implemented in the scheduling of break times.

scholarly journals Collaborative Opportunistic Scheduling in Heterogeneous Networks: A Distributed Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Donglai Sun ◽  
Yang Liu ◽  
Jianhua Li ◽  
Yue Wu
Keyword(s):  
Iterative Algorithm ◽  
Network Model ◽  
Heterogeneous Networks ◽  
Opportunistic Scheduling ◽  
Scheduling Problem ◽  
Decentralized Systems ◽  
Scheduling Scheme ◽  
Distributed Approach ◽  
Total Performance ◽  
Decentralized Mechanism

We consider a collaborative opportunistic scheduling problem in a decentralized network with heterogeneous users. While most related researches focus on solutions for optimizing decentralized systems’ total performance, we proceed in another direction. Two problems are specifically investigated. (1) With heterogenous users having personal demands, is it possible to have it met by designing distributed opportunistic policies? (2) With a decentralized mechanism, how can we prevent selfish behaviors and enforce collaboration? In our research, we first introduce a multiuser network model along with a scheduling problem constrained by individual throughput requirement at each user’s side. An iterative algorithm is then proposed to characterize a solution for the scheduling problem, based on which collaborative opportunistic scheduling scheme is enabled. Properties of the algorithm, including convergence, will be discussed. Furthermore in order to keep the users staying with the collaboration state, an additional punishment strategy is designed. Therefore selfish deviation can be detected and disciplined so that collaboration is enforced. We demonstrate our main findings with both analysis and simulations.

A bicriteria integer programming model for the hierarchical workforce scheduling problem

2010 ◽  
Vol 5 (1) ◽  
pp. 54-62 ◽  
Author(s):  
Rafael Pastor ◽  
Albert Corominas
Keyword(s):  
Integer Programming ◽  
Design Methodology ◽  
Programming Model ◽  
Task Assignment ◽  
Scheduling Problem ◽  
Workforce Scheduling ◽  
Content Type ◽  
Integer Programming Model ◽  
The Cost ◽  
S Model

PurposeThe purpose of this paper is to propose a bicriteria integer programming model for hierarchical workforce scheduling in which the first criterion is the cost and the second is the suitability of task assignment to individual employees. The model is based on the integer programming formulation for the hierarchical workforce scheduling problem published in 2007 by Seçkiner et al., which extends the model proposed by Billionnet in 1999.Design/methodology/approachThe principal hypothesis of this paper is that, although an employee is capable of performing several different tasks with equal efficiency, the type of task to which he/she is assigned affects the overall suitability of the assignment configuration. Therefore, cost‐minimising solutions should also optimise task assignment when possible. This paper considers real cases and confirm that this approach to the problem is appropriate for dealing with common situations in personnel management.FindingsThe proposed idea is applied to the example problem used by Seçkiner et al. and the results are compared with Seçkiner et al.'s model results.Originality/valueConsequently, the proposal is more general and a more faithful representation of the problems faced by personnel managers, which should help to bridge the gap between academic studies and practical cases.

scholarly journals A Successful Three-Phase Metaheuristic for the Shift Minimization Personal Task Scheduling Problem

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Kimmo Nurmi ◽  
Nico Kyngäs
Keyword(s):  
Task Scheduling ◽  
Real World ◽  
Solution Process ◽  
Scheduling Problem ◽  
Workforce Scheduling ◽  
Workload Prediction ◽  
Three Phase ◽  
Benchmark Instances ◽  
Heterogeneous Workforce ◽  
Generation Problem

Workforce scheduling process consists of three major phases: workload prediction, shift generation, and staff rostering. Shift generation is the process of transforming the determined workload into shifts as accurately as possible. The Shift Minimization Personnel Task Scheduling Problem (SMPTSP) is a problem in which a set of tasks with fixed start and finish times must be allocated to a heterogeneous workforce. We show that the presented three-phase metaheuristic can successfully solve the most challenging SMPTSP benchmark instances. The metaheuristic was able to solve 44 of the 47 instances to optimality. The metaheuristic produced the best overall results compared to the previously published methods. The results were generated as a by-product when solving a more complicated General Task-based Shift Generation Problem. The metaheuristic generated comparable results to the methods using commercial MILP solvers as part of the solution process. The presented method is suitable for application in large real-world scenarios. Application areas include cleaning, home care, guarding, manufacturing, and delivery of goods.

Sign in / Sign up

Export Citation Format

Share Document