Latent Class Probabilistic Latent Feature Analysis of Three-Way Three-Mode Binary Data

The analysis of binary three-way data (i.e., persons who indicate which attributes apply to each of a set of objects) may be of interest in several substantive domains as sensory profiling, marketing research or personality assessment. Latent class probabilistic latent feature models (LCPLFMs) may be used to explain binary object-attribute associations on the basis of a small number of binary latent variables (called latent features). As LCPLFMs aim to model object-attribute associations using a small number of latent features they may be more suited to analyze data with many objects/attributes than standard multilevel latent class models which do not include such a dimension reduction. In this paper we describe new functions of the plfm package for analyzing binary three-way data with LCPLFMs. The new functions provide a flexible modeling approach as they allow to (1) specify different assumptions for modeling statistical dependencies between object-attribute pairs, (2) use different assumptions for modeling parameter heterogeneity across persons, (3) conduct a confirmatory analysis by constraining specific parameters to pre-specified values, (4) inspect results with print, summary and plot methods. As an illustration, the models are applied to analyze data on the perception of midsize cars, and to study the situational determinants of anger-related behavior

Integrated personnel planning.

The planning of the workforce in a company is one of the most important problems managers face as labor is very expensive, especially in highly developed countries. It is also one of the most difficult problems to solve as it entails some special features that are absent in all other types of resource allocation problems. When people are involved, the decision environment tends to get very dynamic. In order to fully grasp the problem, one must take into account different employee preferences, labor union constraints, different skills that workers may possess and even the impact that certain decisions may have on the behavior of the employees. As the size of the company increases, this problem tends to get more difficult too. Hence, in order to stay competitive, an efficient personnel planning is indispensable such that demand is met with minimal labor costs and employees stay motivated at the same time. The main idea of this thesis is that applicable solutions to the personnel planning problem can only be obtained by adding realistic assumptions and features. We therefore investigate how elements such as uncertainty, skills, training and even vehicle routing can be integrated with the personnel staffing (i.e., deciding which and how many workers to hire) and scheduling (i.e., deciding when the workers should work and which tasks they should perform) problem. However, taking into account these realistic assumptions highly increases the complexity of the problem. In this thesis we show how our proposed solution techniques can be used to efficiently solve these problems by testing them on real-life situations.nrpages: 279status: publishe

Latent class probabilistic latent feature analysis of three-way three-mode binary data

The analysis of binary three-way data (i.e., persons who indicate which attributes apply to each of a set of objects) may be of interest in several substantive domains as sensory profiling, marketing research or personality assessment. Latent class probabilistic latent feature models (LCPLFMs) may be used to explain binary object-attribute associations on the basis of a small number of binary latent variables (called latent features). As LCPLFMs aim to model object-attribute associations using a small number of latent features they may be more suited to analyze data with many objects/attributes than standard multilevel latent class models which do not include such a dimension reduction. In this paper we describe new functions of the plfm package for analyzing binary three-way data with LCPLFMs. The new functions provide a flexible modeling approach as they allow to (1) specify different assumptions for modeling statistical dependencies between object-attribute pairs, (2) use different assumptions for modeling parameter heterogeneity across persons, (3) conduct a confirmatory analysis by constraining specific parameters to pre-specified values, (4) inspect results with print, summary and plot methods. As an illustration, the models are applied to analyze data on the perception of midsize cars, and to study the situational determinants of anger-related behavior.status: publishe

Automated cargo bundling for SMEs

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Automated cargo bundling for SMEs

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Comparison of support policies for residential photovoltaic systems in the major EU markets through investment profitability

In this paper a comprehensive evaluation of the support policy for photovoltaic installations in the residential sector of the major European markets (Flanders (Belgium), Germany, Italy, Spain and France) is carried out. To this end, the economic viability of a household investment in a photovoltaic installation is studied, employing a model based on the discounted cash flows of the installation over its lifetime. The results indicate that Italy's support system has been the most profitable out of the countries studied since 2010. In general, under current support policies, residential installations are still profitable in most cases, despite decreasing support levels, except for Spain. Furthermore, the paper demonstrates that self-consumption can significantly increase profits, especially in Spain and Germany. However, Flanders' policy has no effect on levels of self-consumption. Finally, a comparison of past and present policies shows the varying levels of success countries have enjoyed in keeping the profitability of investments stable over the years, depending on the efficiency of their support policy. Germany's support system might be considered the most balanced one over the last five years.publisher: Elsevier articletitle: Comparison of support policies for residential photovoltaic systems in the major EU markets through investment profitability journaltitle: Renewable Energy articlelink: http://dx.doi.org/10.1016/j.renene.2015.09.063 content_type: article copyright: Copyright © 2015 Elsevier Ltd. All rights reserved.status: publishe

A Model Enhancement Approach for Optimizing the Integrated Shift Scheduling and Vehicle Routing Problem in Waste Collection

© 2017 Elsevier B.V. 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.status: publishe

Workforce planning incorporating skills: state of the art

This paper presents a review and classification of the literature regarding workforce planning problems incorporating skills. In many cases, technical research regarding workforce planning focuses very hard on the mathematical model and neglects the real life implications of the simplifications that were needed for the model to perform well. On the other hand, many managerial studies give an extensive description of the human implications of certain management decisions in particular cases, but fail to provide useful mathematical models to solve workforce planning problems. This review will guide the operations researcher in his search to find useful papers and information regarding workforce planning problems incorporating skills. We not only discuss the differences and similarities between different papers, but we also give an overview of the managerial insights. The objective is to present a combination of technical and managerial knowledge to encourage the production of more realistic and useful solution techniques.nrpages: 38status: publishe

A two-stage mixed integer programming approach for optimizing the skill mix and training schedules for aircraft maintenance

This paper presents a two-stage mixed integer programming approach for optimizing the skill mix and training schedule at the aircraft maintenance company Sabena Technics. Of course, when all workers are trained for all skills, cheaper workforce schedules are possible. However, the training that is required to acquire all those skills can become very expensive. In the first stage of our two-staged approach, we therefore make a trade-off between the training costs and the resulting cheaper workforce schedule. As we assume that workers are unavailable to work during their training, the obtained result is only applicable in practice if the required training can be performed without endangering the current maintenance operations. In the second stage, we therefore want to find an optimal and feasible training schedule in order to obtain the desired skill mix with minimal costs. We illustrate our models with a computational experiment based on real-life data of Sabena Technics.nrpages: 32status: publishe