Imma Ribas

Review: Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective

In this paper, an extensive review of recently published papers on hybrid flow shop (HFS) scheduling problems is presented. The papers are classified first according to the HFS characteristics and production limitations considered in the respective papers. This represents a new approach to the classification of papers in the HFS environment. Second, the papers have been classified according to the solution approach proposed. These two classification categories give a comprehensive overview on the state of the art of the problem and can guide the reader with respect to future research work.

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.

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.

Efficient heuristic algorithms for the blocking flow shop scheduling problem with total flow time minimization

Two efficient constructive heuristics for the Fm|block|ΣCi are proposed.We show that the insertion phase of heuristic NEH can worsen the solution.The structure of each constructive method is used in a GRASP combined with VNS.The computational evaluation shows the good performance of these algorithms. This paper proposes two constructive heuristics, i.e. HPF1 and HPF2, for the blocking flow shop problem in order to minimize the total flow time. They differ mainly in the criterion used to select the first job in the sequence since, as it is shown, its contribution to the total flow time is not negligible. Both procedures were combined with the insertion phase of NEH to improve the sequence. However, as the insertion procedure does not always improve the solution, in the resulting heuristics, named NHPF1 and NHPF2, the sequence was evaluated before and after the insertion to keep the best of both solutions. The structure of these heuristics was used in Greedy Randomized Adaptive Search Procedures (GRASP) with variable neighborhood search in the improvement phase to generate greedy randomized solutions. The performance of the constructive heuristics and of the proposed GRASPs was evaluated against other heuristics from the literature. Our computational analysis showed that the presented heuristics are very competitive and able to improve 68 out of 120 best known solutions of Taillards instances for the blocking flow shop scheduling problem with the total flow time criterion.

Methodological elements of supply chain design

After a discussion of the methodological proposals for supply chain (SC) design published so far, we describe a hierarchical method consisting of five stages, as well as related concepts and tools. The aim of this method, named SC outline process, is to provide a frame for the decision-making about the SC configuration. This approach is applicable for all types of SCs.

Efficient constructive procedures for the distributed blocking flow shop scheduling problem

The distributed blocking flow shop scheduling problem (DBFSP) allows modeling of the scheduling process in companies with more than one factory, with productive systems configured as flow shop lines where the blocking constraint has to be considered. To the best of our knowledge, this variant of the distributed permutation flow shop scheduling problem has not been studied. In this paper, we propose some constructive heuristics that will solve the DBFSP and thus minimize the maximum completion time among the factories. The proposed procedures use two approaches that are totally different from those proposed for the distributed permutation flow shop scheduling problem (DPFSP). By taking the DPFSP procedures that we adapted to DBFSP and comparing them to the new approaches that were specifically designed for DBPFSP, we find that the latter perform considerably better.

Note on the behaviour of an improvement heuristic on permutation and blocking flow-shop scheduling

This work deals with the permutation flow-shop scheduling problem with and without storage space between stages, where the performance criterion is the makespan. Many proposed procedures to solve these problems have an improvement phase based on the search in the pair-wise interchange neighbourhood. The authors have observed large plateaus in the solutions domain of these problems defined for this type of neighbourhood that make it difficult for the heuristics to search for a road to the optimum. An improvement heuristic is proposed, which uses two tools in order to evade these difficulties: a stochastic exploration of the neighbourhood (revolver) and a special consideration of ties. The improvement heuristic is applied, in conjunction with three adapted well-known heuristics in the literature, to the direct and inverse instances. The performance of the procedures was evaluated on nine generated sets of a thousand instances and on 90 instances from Taillard (1993). The obtained results recommend applying always the constructive heuristic procedures on the direct and inverse instance. The computational experience proves the effectiveness of the two tools implemented in the improvement phase.