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Pereira, J. (2016). Procedures for the bin packing problem with precedence constraints. Eur. J. Oper. Res., 250(3), 794–806.
Abstract: The bin packing problem with precedence constraints (BPP-P) is a recently proposed variation of the classical bin packing problem (BPP), which corresponds to a basic model featuring many underlying characteristics of several scheduling and assembly line balancing problems. The formulation builds upon the BPP by incorporating precedence constraints among items, which force successor items to be packed into later bins than their predecessors. In this paper we propose a dynamic programming based heuristic, and a modified exact enumeration procedure to solve the problem. These methods make use of several new lower bounds and dominance rules tailored for the problem in hand. The results of a computational experiment show the effectiveness of the proposed methods, which are able to close all of the previous open instances from the benchmark instance set within very reduced running times. (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.
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Pereira, J. (2018). Modelling and solving a cost-oriented resource-constrained multi-model assembly line balancing problem. Int. J. Prod. Res., 56(11), 3994–4016.
Abstract: A line balancing problem considers the assignment of operations to workstations in an assembly line. While assembly lines are usually associated to mass production of standardised goods, their advantages have led to their widespread use whenever a product-oriented production system is applicable and the benefits of the labour division and specialisation are significant, even when some of its characteristics may deviate from classical assembly lines. In this work, we study a line balancing problem found in the textile industry in which the line must be balanced for multiple types of goods taking into account resource requirements. In order to solve the problem, a hybrid method that combines classical methods for line balancing with an Estimation of Distribution Algorithm is proposed. Computational experiments show that the new procedure improves upon the state of the art when compared using a benchmark set derived from the literature, as well as when compared using data from the manufacturer that originated this research work.
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Pereira, J., & Alvarez-Miranda, E. (2018). An exact approach for the robust assembly line balancing problem. Omega-Int. J. Manage. Sci., 78, 85–98.
Abstract: This work studies an assembly line balancing problem with uncertainty on the task times. In order to deal with the uncertainty, a robust formulation to handle changes in the operation times is put forward. In order to solve the problem, several lower bounds, dominance rules and an enumeration procedure are proposed. These methods are tested in a computational experiment using different instances derived from the literature and then compared to similar previous approaches. The results of the experiment show that the method is able to solve larger instances in shorter running times. Furthermore, the cost of protecting a solution against uncertainty is also investigated. The results highlight that protecting an assembly line against moderate levels of uncertainty can be achieved at the expense of small quantities of additional resources (stations). (C) 2017 Elsevier Ltd. All rights reserved.
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