The Single-Vehicle Cyclic Inventory Routing Problem (SV-CIRP) belongs to the class of Inventory Routing Problems (IRP) in which the supplier optimises both the distribution costs and the inventory costs at the customers. The goal of the SV-CIRP is to minimise both kinds of costs and to maximise the collected rewards, by selecting a subset of customers from a given set and determining the quantity to be delivered to each customer and the vehicle routes, while avoiding stockouts. A cyclic distribution plan should be developed for a single vehicle.; We present an iterated local search (ILS) metaheuristic that exploits typical characteristics of the problem and opportunities to reduce the computation time. Experimental results on 50 benchmark instances show that our algorithm improves the results of the best available algorithm on average with 16.02%. Furthermore, 32 new best known solutions are obtained. A sensitivity analysis demonstrates that the performance of the algorithm is not influenced by small changes in the parameter settings of the ILS. (C) 2014 Elsevier B.V. All rights reserved.Peer ReviewedPostprint (published version

Iterated local search (ILS) is a powerful framework for developing efficient algorithms for the permutation\ud flow-shop problem (PFSP). These algorithms are relatively simple to implement and use very few parameters,\ud which facilitates the associated fine-tuning process. Therefore, they constitute an attractive solution for real-\ud life applications. In this paper, we discuss some parallelization, parametrization, and randomization issues\ud related to ILS-based algorithms for solving the PFSP. In particular, the following research questions are\ud analyzed: (a) Is it possible to simplify even more the parameter setting in an ILS framework without affecting\ud performance? (b) How do parallelized versions of these algorithms behave as we simultaneously vary the\ud number of different runs and the computation time? (c) For a parallelized version of these algorithms, is it\ud worthwhile to randomize the initial solution so that different starting points are considered? (d) Are these\ud algorithms affected by the use of a “good-quality” pseudorandom number generator? In this paper, we\ud introduce the new ILS-ESP (where ESP is efficient, simple, and parallelizable) algorithm that is specifically\ud designed to take advantage of parallel computing, allowing us to obtain competitive results in “real time”\ud for all tested instances. The ILS-ESP also uses “natural” parameters, which simplifies the calibration process.\ud An extensive set of computational experiments has been carried out in order to answer the aforementioned\ud research questionsPeer ReviewedPostprint (published version

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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.Peer ReviewedPostprint (author’s final draft