Time filter

Source Type

Braekers K.,Hasselt University | Braekers K.,Research Foundation Flanders FWO | Ramaekers K.,Hasselt University | Van Nieuwenhuyse I.,Research Center for Operations Management
Computers and Industrial Engineering | Year: 2015

Over the past decades, the Vehicle Routing Problem (VRP) and its variants have grown ever more popular in the academic literature. Yet, the problem characteristics and assumptions vary widely and few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the VRP literature published between 2009 and June 2015. Based on an adapted version of an existing comprehensive taxonomy, we classify 277 articles and analyze the trends in the VRP literature. This classification is the first to categorize the articles to this level of detail. © 2015 Elsevier Ltd. Source

Wang J.,National University of Defense Technology | Wang J.,Research Center for Operations Management | Demeulemeester E.,Research Center for Operations Management | Qiu D.,National University of Defense Technology
Computers and Operations Research | Year: 2016

Most earth observation satellites (EOSs) are equipped with optical sensors, which cannot see through clouds. Hence, observations are significantly affected and blocked by clouds. In this work, with the inspiration of the notion of a forbidden sequence, we propose a novel assignment formulation for EOS scheduling. Considering the uncertainties of clouds, we formulate the cloud coverage for observations as stochastic events, and extend the assignment formulation to a chance constraint programming (CCP) model. To solve the problem, we suggest a sample approximation (SA) method, which transforms the CCP model into an integer linear programming (ILP) model. Subsequently, a branch and cut (B&C) algorithm based on lazy constraint generation is developed to solve the ILP model. Finally, we conduct a lot of simulation experiments to verify the effectiveness and efficiency of our proposed formulation and algorithm. © 2016 Elsevier Ltd. All rights reserved. Source

Lamas P.,Research Center for Operations Management | Demeulemeester E.,Research Center for Operations Management
Journal of Scheduling | Year: 2015

The purpose of this research is to develop a new procedure for generating a proactive baseline schedule for the resource-constrained project scheduling problem. The main advantage of this new procedure is that it is completely independent of the reactive policy applied. This contrasts with the traditional methods that assume a predefined reactive policy. First, we define a new robustness measure, then we introduce a branch-and-cut method for solving a sample average approximation of our original problem. In a computational experiment, we show that our procedure outperforms two other published methods, assuming different robustness measures. © 2015 Springer Science+Business Media New York Source

Colen P.J.,Research Center for Operations Management | Lambrecht M.R.,Research Center for Operations Management
International Journal of Production Economics | Year: 2012

To evaluate the outcomes of deploying technicians dedicated to preventive maintenance, instead of fully cross-trained technicians, this simulation study assesses field service operations of a company selling maintenance services. Comprehensive service contracts render the maintenance demand experienced by the field service organization dependent on the cross-training decision. The optimal cross-training policy and the factors that influence this policy are determined, taking into account the effect on the demand for maintenance. Evidence shows that full cross-training might be especially beneficial in a field service setting. In many of the tested scenarios, full cross-training is optimal or the optimal fraction of the workforce being dedicated is low. The results reveal that, in general, a higher workload, more reliable machines, a higher maintenance frequency, and a higher contract coverage increase the benefits of deploying dedicated technicians. © 2012 Elsevier B.V. All rights reserved. Source

Belien J.,Center for Modeling and Simulation | Belien J.,Research Center for Operations Management | De Boeck L.,Center for Modeling and Simulation | De Boeck L.,Research Center for Operations Management | And 5 more authors.
Decision Support Systems | Year: 2013

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 recipient's body. The weight factor for the elapsed time before the organ's 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 organ's 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. © 2012 Elsevier B.V. Source

Discover hidden collaborations