A greedy heuristic approach for the project scheduling with labour allocation problem

Responding to the growing need of generating a robust project scheduling, in this article we present a greedy algorithm to generate the project baseline schedule. The robustness achieved by integrating two dimensions of the human resources flexibilities. The first is the operators’ polyvalence, i.e. each operator has one or more secondary skill(s) beside his principal one, his mastering level being characterized by a factor we call “efficiency”. The second refers to the working time modulation, i.e. the workers have a flexible time-table that may vary on a daily or weekly basis respecting annualized working strategy. Moreover, the activity processing time is a non-increasing function of the number of workforce allocated to create it, also of their heterogynous working efficiencies. This modelling approach has led to a nonlinear optimization model with mixed variables. We present: the problem under study, the greedy algorithm used to solve it, and then results in comparison with those of the genetic algorithms

Development and validation of resource flexibility measures for manufacturing industry

Purpose: Global competition and ever changing customers demand have made manufacturing organizations to rapidly adjust to complexities, uncertainties, and changes. Therefore, flexibility in manufacturing resources is necessary to respond cost effectively and rapidly to changing production needs and requirements. Ability of manufacturing resources to dynamically reallocate from one stage of a production process to another in response to shifting bottlenecks is recognized as resource flexibility. This paper aims to develop and validate resource flexibility measures for manufacturing industry that could be used by managers/ practitioners in assessing and improving the status of resource flexibility for the optimum utilization of resources. Design/methodology/approach: The study involves survey carried out in Indian manufacturing industry using a questionnaire to assess the status of various aspects of resource flexibility and their relationships. A questionnaire was specially designed covering various parameters of resource flexibility. Its reliability was checked by finding the value of Cronback alpha (0.8417). Relative weightage of various measures was found out by using Analytical Hierarchy Process (AHP). Pearson’s coefficient of correlation analysis was carried out to find out relationships between various parameters. Findings: From detailed review of literature on resource flexibility, 17 measures of resource flexibility and 47 variables were identified. The questionnaire included questions on all these measures and parameters. ‘Ability of machines to perform diverse set of operations’ and ability of workers to work on different machines’ emerged to be important measures with contributing weightage of 20.19% and 17.58% respectively. All the measures were found to be significantly correlated with overall resource flexibility except ‘training of workers’, as shown by Pearson’s coefficient of correlation. This indicates that companies do not want to spend on worker training. Practical implications: The study provides guidelines to managers/ practitioners in assessing and managing resource flexibility for optimum utilization of resources. This study can also help the firm’s management to identify the measures and variables to manage resource flexibility and the order in which stress should be given to various measures and actions. The developed and validated measures can be used globally for managing the resource flexibility in manufacturing sector. Originality/value: In this work, the theoretical perspective has been used to prepare the instrument from a detailed review of literature and then the study carried out using the questionnaire in an area where such studies were not carried out earlier.Peer Reviewe

Simulation analysis of resource flexibility on healthcare processes

Purpose: This paper uses discrete event simulation to explore the best resource flexibility scenario and examine the effect of implementing resource flexibility on different stages of patient treatment process. Specifically we investigate the effect of resource flexibility on patient waiting time and throughput in an orthopedic care process. We further seek to explore on how implementation of resource flexibility on patient treatment processes affects patient access to healthcare services. We focus on two resources, namely, orthopedic surgeon and operating room. Methods: The observational approach was used to collect process data. The developed model was validated by comparing the simulation output with actual patient data collected from the studied orthopedic care process. We developed different scenarios to identify the best resource flexibility scenario and explore the effect of resource flexibility on patient waiting time, throughput, and future changes in demand. The developed scenarios focused on creating flexibility on service capacity of this care process by altering the amount of additional human resource capacity at different stages of patient care process and extending the use of operating room capacity. Results: The study found that resource flexibility can improve responsiveness to patient demand in the treatment process. Testing different scenarios showed that the introduction of resource flexibility reduces patient waiting time and improves throughput. The simulation results show that patient access to health services can be improved by implementing resource flexibility at different stages of the patient treatment process. Conclusion: This study contributes to the current health care literature by explaining how implementing resource flexibility at different stages of patient care processes can improve ability to respond to increasing patients demands. This study was limited to a single patient process; studies focusing on additional processes are recommended. Keywords: agile strategy, waiting time, throughput, patient access, responsivenesspublishedVersio

Odnos između složenosti i fleksibilnosti proizvodnih struktura

The aim of this paper is to contribute to the development of procedures for the design of effective production structures of an enterprise. In order to do this, the paper focuses on two main aspects. Firstly, the paper considers the possibilities of making production structures more manageable by means of lowering the degree of complexity of those structures. Secondly, the focus is on ways of enabling those structures to adapt to changes in the environment, i.e. on flexibility. Complexity of a production structure is a characteristic defined by the number of structural elements and their interdependence. Flexibility of production structures is observed through three components: technological component, capacity component and flexibility of flows.Cilj članka je prilog razvoju postupaka za dizajniranje efektivnih proizvodnih struktura poduzeća. U tom smislu člnak se fokusira na dva bitna aspekta: prvi je razmatranje mogućnosti uspostavljanja proizvodnih struktura visoke pogodnosti upravljanja putem sniženja stupnja njihove složenosti, a drugi je dizajniranje proizvodnih struktura osposobljenih za prilagođavanje promjenama u okolini, odnosno za potrebnu i dovoljnu fleksibilnost. Složenost proizvodnih struktura se definira putem broja elemenata strukture i njihovim međusobnim uvjetovanjem, dok se fleksibilnost proizvodnih struktura razmatra u svjetlu tri komponente: tehnološke komponente, kapacitivne komponente i fleksibilnosti proizvodnih tokova

The division of labour under uncertainty

Reductions in the division of labour are a significant feature of modern developments in work organisation. It has been recognised that a reduced division of labour can have the advantages of job enrichment and lower coordination costs. In this paper it is shown how advantages from a lesser division of labour can stem from the flow of work between different sets of resources where the work rates of individual production stages are subject to uncertainties. Both process and project-based work are considered. Implications for the boundaries of the firm and for innovation processes are noted

Calibrating cross-training to meet demand mix variation and employee absence

We address the problem of determining the cross-training that a work team needs in order to cope with demand mix variation and absences. We consider the case in which all workers can be trained on all tasks, the workforce is a resource that determines the capacity and a complete forecasting of demand is not available. The demand mix variation that the organization wants to be able to cope with is fixed by establishing a maximum time to devote to each product. We contend that this approach is straightforward, has managerial practicality and can be applied to a broad range of practical scenarios. It is required that the demand mix variation be met, even if there are a certain level of absences. To numerically solve the mathematical problem, a constraint-based selection procedure is developed, which we term CODEMI. We provide illustrated examples demonstrating solution quality for the approximation, and we report on an illustrative set of computational cases. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.Peer ReviewedPostprint (published version

An integrated personnel allocation and machine scheduling problem for industrial size multipurpose plants

This paper describes the development and implementation of an optimization model to solve the integrated problem of personnel allocation and machine scheduling for industrial size multipurpose plants. Although each of these problems has been extensively studied separately, works that study an integrated approach are very limited, particularly for large-scale industrial applications. We present a mathematical formulation for the integrated problem and show the results obtained from solving large size instances from an analytical services facility. The integrated formulation can improve the results up to 22.1% compared to the case where the personnel allocation and the machine scheduling problems are solved sequentially

Étude de la flexibilité opérationnelle d’un flow shop par des algorithmes génétiques

Dans un récent article nous avons resolu le problème de la flexibilité opérationnelle d’un « flow shop » en prenant en compte la flexibilité à l’aide d’une méthode exacte. Ce qui a permis d’obtenir une solution optimale, mais au prix d’un temps de résolution relativement grand, trop important pour une gestion d’atelier en temps réel. Le problème à résoudre est de caractériser les leviers de flexibilité liés à la variation des durées opératoires et des dates de livraison des articles d’un atelier de production à cheminement unique afin d’assurer la flexibilité opérationnelle du système. Dans le présent travail, nous utilisons cette fois les algorithmes génétiques pour approcher la solution optimale en recherchant un temps de résolution plus court. Il s’agit dans cet article d’exposer cette résolution et de présenter une comparaison avec celle de la méthode exacte précédemment utilisé

Ordonnancement d'atelier et ressources humaines: affectation des opérateurs dans un flowshop

Cet article aborde le problème de l'ordonnancement d'un atelier de type flowshop, lorsque les durées opératoires varient suivant quel opérateur travaille sur quelle machine. La prise en compte de cette notion de performance ajoute l'affectation des opérateurs au problème d’ordonnancement, qui ne se résume plus à une recherche de séquence de passage des travaux sur les machines. Une heuristique basée sur une règle d'affectation "intuitive" généralement utilisée est évaluée, puis une borne inférieure du problème complet est présentée. Cette borne permet de faire apparaître certaines caractéristiques des règles d’affectation