Xavier Tort-Martorell

An efficient Discrete Artificial Bee Colony algorithm for the blocking flow shop problem with total flowtime minimization

A high performing DABC algorithm is proposed for the Fm|block|ΣCi.An efficient procedure to generate the initial food sources is presented.Some strategies for each phase of the algorithm were tested.The selection of the best strategies was decided by means a design of experiments. This paper presents a high performing Discrete Artificial Bee Colony algorithm for the blocking flow shop problem with flow time criterion. To develop the proposed algorithm, we considered four strategies for the food source phase and two strategies for each of the three remaining phases (employed bees, onlookers and scouts). One of the strategies tested in the food source phase and one implemented in the employed bees phase are new. Both have been proved to be very effective for the problem at hand. The initialization scheme named HPF2(λ,µ) in particular, which is used to construct the initial food sources, is shown in the computational evaluation to be one of the main procedures that allow the DABC_RCT to obtain good solutions for this problem. To find the best configuration of the algorithm, we used design of experiments (DOE). This technique has been used extensively in the literature to calibrate the parameters of the algorithms but not to select its configuration. Comparing it with other algorithms proposed for this problem in the literature demonstrates the effectiveness and superiority of the DABC_RCT.

Comparing three-step heuristics for the permutation flow shop problem

In this paper a three steps heuristic for the permutation flow shop problem is proposed. The objective is to minimize the maximum time for completing the jobs, or the makespan. The first two steps are inspired by the NEH heuristic, to which a new tie breaking strategy has been incorporated in the insertion phase. Furthermore, the reversibility property of the problem dealt with is taken as a tool for improving the obtained solution. The third step consists of an iterated local search procedure with an embedded local search which is a variant of the non exhaustive descent algorithm. The statistical analysis of the results shows the effectiveness of the proposed procedures.

A competitive variable neighbourhood search algorithm for the blocking flow shop problem

This paper analyses the performance of two variable neighbourhood search (VNS) methods for the Fm | block | Cmax problem. The main difference between both is the strategy used to change the neighbourhood in the improvement phase. The first strategy, named parallel version, randomly chooses between swap and insertion neighbourhoods to improve the solution. The second strategy, named serial version, begins the search in one of the neighbourhoods and continues the search in the other one. Additionally, we have analysed and improved the effectiveness of several NEH-based procedures to generate the initial solution. Moreover, we have tested each VNS strategy with two types of local search which led us to define four procedures that were tested with the Taillard benchmark and with a test-bed created ad hoc. The computational evaluation showed that these algorithms and especially the serial VNS which uses PW/PWE2 to generate the initial solution would be very competitive.

Six Sigma: : hints from practice to overcome difficulties

Six Sigma has proven to be a powerful system for improving quality and productivity. However, the successful implementation of the methodology is not simple, and it is therefore normal – especially in the early phases – to experience problems that may impede taking full advantage of the methodology. We have grouped some of the most frequent ones into four main areas: implementation and organisational aspects, adherence to DMAIC methodology, tools and statistical techniques and implementation of improvements and project closure. For each of them, the paper discusses some of the difficulties and issues that should be taken into account.

An efficient iterated local search algorithm for the total tardiness blocking flow shop problem

This paper deals with the blocking flow shop problem and proposes an Iterated Local Search (ILS) procedure combined with a variable neighbourhood search (VNS) for the total tardiness minimisation. The proposed ILS makes use of a NEH-based procedure to generate the initial solution, and uses a local search to intensify the exploration that combines the insertion and swap neighbourhood and uses a perturbation mechanism consisting of three neighbourhood operators to diversify the search. The computational evaluation has shown the effectiveness of combining the insertion and swap neighbourhood during the search despite the insertion neighbourhood being more effective than the swap neighbourhood for this problem. Finally, the computation of this algorithm when evaluated against two other algorithms from the literature shows good performance.

Efficient heuristics for the parallel blocking flow shop scheduling problem

New Constructive heuristic for both the PBFSP and the DBFSP.Combination of IGA and ILS methods with two types of VNS.A MILP model solved for small-sized instances.The proposed methods are very effective. We consider the NP-hard problem of scheduling n jobs in F identical parallel flow shops, each consisting of a series of m machines, and doing so with a blocking constraint. The applied criterion is to minimize the makespan, i.e., the maximum completion time of all the jobs in F flow shops (lines). The Parallel Flow Shop Scheduling Problem (PFSP) is conceptually similar to another problem known in the literature as the Distributed Permutation Flow Shop Scheduling Problem (DPFSP), which allows modeling the scheduling process in companies with more than one factory, each factory with a flow shop configuration. Therefore, the proposed methods can solve the scheduling problem under the blocking constraint in both situations, which, to the best of our knowledge, has not been studied previously. In this paper, we propose a mathematical model along with some constructive and improvement heuristics to solve the parallel blocking flow shop problem (PBFSP) and thus minimize the maximum completion time among lines. The proposed constructive procedures use two approaches that are totally different from those proposed in the literature. These methods are used as initial solution procedures of an iterated local search (ILS) and an iterated greedy algorithm (IGA), both of which are combined with a variable neighborhood search (VNS). The proposed constructive procedure and the improved methods take into account the characteristics of the problem. The computational evaluation demonstrates that both of them -especially the IGA- perform considerably better than those algorithms adapted from the DPFSP literature.

Experimentation order with good properties for 2k factorial designs

Randomizing the order of experimentation in a factorial design does not always achieve the desired effect of neutralizing the influence of unknown factors. In fact, with some very reasonable assumptions, an important proportion of random orders achieve the same degree of protection as that obtained by experimenting in the design matrix standard order. In addition, randomization can induce a large number of changes in factor levels and thus make experimentation expensive and difficult. De Leon et al. [Experimentation order in factorial designs with 8 or 16 runs, J. Appl. Stat. 32 (2005), pp. 297–313] proposed experimentation orders for designs with eight or 16 runs that combine an excellent level of protection against the influence of unknown factors, with the minimum number of changes in factor levels. This article presents a new methodology to obtain experimentation orders with the desired properties for designs with any number of runs.

Design of experimental studies for measurement and evaluation of the determinants of Job Satisfaction

In this paper the authors examine the methodology of data analysis and collection usually applied in Job-Satisfaction studies and more generally in Well-being research. In this field, data is collected through questionnaires and analysed using multivariate statistical techniques, a process which is commonly known as non-experimental research. The article points out some of the problems in this procedure and proposes an alternative experimental methodology which is applied to evaluate Job-Satisfaction over a Dutch random sample. Essentially it consists of the implementation of factorial designs in questionnaire construction. The use of fractional factorials is also discussed.

A Methodology to Model Water Demand based on the Identification of Homogenous Client Segments. Application to the City of Barcelona

Water management has become a vital concern for both water supply companies and public administrations due to the importance of water for life and current scarcity in many areas. Studies exist that attempt to explain which factors influence water demand. In general, these studies are based on a small sample of consumers and they predict domestic water consumption using ordinary least squares regression models with a small number of socioeconomic variables as predictors, usually: price, population, population density, age, and nationality. We have followed a different approach in two ways; one, in the scope of the study: we have included in the study all consumers of the Barcelona area and as many socioeconomic variables as possible (all the available data from official statistics institutions); and also in the methodology: first, we have segmented clients into homogeneous socioeconomic groups that, as we show later in the Barcelona case, also have homogeneous water consumption habits. This allows for a better understanding of water consumption behaviours and also for better predictions through modeling water consumption in each segment. This is so because the segments’ inner variability is smaller than the general one; thus, the models have a smaller residual variance and allow for more accurate forecasts of water consumption. The methodology was applied to the Barcelona metropolitan area, where it was possible to construct a database including both water consumption and socioeconomic information with more than one million observations. Data quality was a primary concern, and thus a careful exploratory data analysis procedure led to a careful treatment of missing observations and to the detection and correction or removal of anomalies. This has resulted in a stable division of the one million water consumers into 6 homogeneous groups and models for each of the groups. Although the methodology has been developed and applied to the Barcelona area, it is general and thus can be applied to any other region or metropolitan area.

Experimentation order in factorial designs: new findings

Under some very reasonable hypotheses, it becomes evident that randomizing the run order of a factorial experiment does not always neutralize the effect of undesirable factors. Yet, these factors do have an influence on the response, depending on the order in which the experiments are conducted. On the other hand, changing the factor levels is many times costly; therefore it is not reasonable to leave to chance the number of changes necessary. For this reason, run orders that offer the minimum number of factor level changes and at the same time minimize the possible influence of undesirable factors on the experimentation have been sought. Sequences which are known to produce the desired properties in designs with 8 and 16 experiments can be found in the literature. In this paper, we provide the best possible sequences for designs with 32 experiments, as well as sequences that offer excellent properties for designs with 64 and 128 experiments. The method used to find them is based on a mixture of algorithmic searches and an augmentation of smaller designs.