Liesje De Boeck

Personnel scheduling: A literature review

This paper presents a review of the literature on personnel scheduling problems. Firstly, we discuss the classification methods in former review papers. Secondly, we evaluate the literature in the many fields that are related to either the problem setting or the technical features. Each perspective is presented as a table in which the classification is displayed. This method facilitates the identification of manuscripts related to the reader’s specific interests. Throughout the literature review, we identify trends in research on personnel staffing and scheduling, and we indicate which areas should be subject to future research.

Municipal Solid Waste Collection and Management Problems: A Literature Review

This paper presents a review of the available literature on solid waste management problems, with a particular focus on vehicle routing problems. The available papers are classified into different categories with the purpose of providing the reader with a guide that facilitates his or her search for papers in his or her field of interest. For each category, a table is presented that gives a summary of how each paper scores from that perspective. Additional explanation is presented about the characteristics of each category using some key references. Finally, this paper discovers unexplored areas of research and identifies trends in the literature.

Advanced resource planning as a decision support module for ERP

The planning and decision support capabilities of the manufacturing planning and control system, which provides the core of any enterprise resource planning package, can be enhanced substantively by the inclusion of a decision support module as an add-on at the midterm planning level. This module, called advanced resource planning (ARP), provides a parameter-setting process, with the ultimate goal of yielding realistic information about production lead times for scheduling purposes, sales and marketing, strategic and operational decision making, and suppliers and customers. This article illustrates the ARP approach with reports from several real-life implementations by large industrial companies.

An open queueing network for lead time analysis

Abstract In this paper we develop an open queueing network for a multi-product multi-machine job-shop in a make-to-order environment. The job-shop produces a variety of products which are characterized by individual general arrival rates and individual general production rates for the machines on their deterministic routings. By incorporating the machines into a general open queueing network, we obtain the average, variance and probability distribution of the individual product lead times, The open queueing network will be illustrated by application to a real-life example existing at Recticcl Bedding Hulshout. In addition to using a flexible and computational efficient approach, we methodologically reveal that the approximate queueing network is suitable lo rapidly provide an answer to managerial questions.

Optimizing the facility location design of organ transplant centers

This paper presents a mixed integer linear programming (MILP) long-term decision model to optimize the location of organ transplant centers. The objective is to minimize the sum of the weighted time components between the moment a donor organ becomes available and its transplantation into the recipients body. The weight factor for the elapsed time before the organs removal from the donor body allows to assign a lower weight to this time component in the objective function in order to reflect the criticality of the process after the organs removal. The specificity of organ transplants makes the model more complex than a traditional facility location model. The model is applied to the Belgian organ transplant path. Extensive numerical experiments reveal the key factors that impact the long-term decision of centralizing versus decentralizing transplant centers.

A three-stage approach for aircraft line maintenance personnel rostering using MIP, discrete event simulation and DEA

Personnel scheduling problems need to cope with personnel preferences, coverage constraints, legal restrictions, and many other constraints. We present a three-stage methodology that can be used to select personnel rosters. In the first stage we generate multiple personnel rosters with a mathematical programming model. In the second stage, the performance of the rosters regarding a number of service criteria is evaluated through discrete event simulation. In the third stage, a ranking is made using data envelopment analysis. The methodology is tested on a personnel scheduling problem for aircraft line maintenance.

Using Mixed-Integer Programming to Win a Cycling Game

This paper presents an application of optimization modeling to the winning of a popular cycling game. The application includes real-life data of contempory cyclists. It also has the potential to motivate students with a competitive but fun “race” for a solution. Because the developed optimization model contains features of knapsack problems, multiperiod inventory problems, and logical constraint modeling, it is perfectly suitable for a concluding case study in an undergraduate operations research/management science course. The application was originally developed for an MBA operations research course focusing on spreadsheet modeling skills, but it can also be used in courses that focus on algebraic modeling of optimization problems.

Teaching Integer Programming Starting From an Energy Supply Game

This paper presents an integer programming IP model for solving an online energy supply game. Instead of a traditional approach in which students are given a problem statement and asked to develop an IP model, both the problem and data are hidden in the game. The energy supply game can be used to illustrate many mathematical programming concepts including blending constraints, multiobjective programming, and the branch-and-bound method. In addition to developing IP modeling skills, students become familiar with the properties of several energy supply systems. The results of two experiments and the related evaluation questionnaires indicate that the game component motivates students more to build IP models as compared to classic approaches.

A column generation approach for solving the examination-timetabling problem

In this paper, we approach the Examination-Timetabling Problem (ETP) from a student-centric point of view. We allow for multiple versions of an exam to be scheduled to increase the spreading of exams for students. We propose two Column Generation (CG) algorithms. In the first approach, a column is defined as an exam schedule for every unique student group, and a Pricing Problem (PPs) is developed to generate these columns. The Master Program (MP) then selects an exam schedule for every unique student group. Instead of using branch-and-price, we heuristically select columns. In the second approach, a column consists of a mask schedule for every unique student group, and a PP is developed to generate the masks. The MP then selects the masks and schedules exams in the mask slots. We compare both models and perform a computational experiment. We solve the ETP at KU Leuven campus Brussels (Belgium) for the business engineering degree program and apply the models to two existing datasets from the literature.

A model enhancement approach for optimizing the integrated shift scheduling and vehicle routing problem in waste collection

Abstract This paper presents a model enhancement approach for the integrated problem of developing shift schedules and waste collection routes. Given a variable amount of waste to be collected the objective is to find fixed, minimal cost shift schedules and collection routes under a service level constraint. While regular shifts during traffic peak hours are cheaper in terms of labour costs, the collection speed is on average lower than during expensive, non-regular shifts. Our findings can be summarized as follows. (1) Solutions can be found within reasonable computation time for real-life instances. (2) The model enhancement approach accurately estimates the required collection times and therefore consistently finds a feasible solution. (3) The solutions not only result in considerable savings, but are also proven to be (near)optimal by comparison with a practical lower bound based on flexible routes.