Showing papers in "European Journal of Operational Research in 2005"

TL;DR: This paper proposes a stochastic programming model and solution algorithm for solving supply chain network design problems of a realistic scale and integrates a recently proposed sampling strategy, the sample average approximation scheme, with an accelerated Benders decomposition algorithm to quickly compute high quality solutions.

TL;DR: In this article, the authors present a review of the state-of-the-art in continuous location models and network location models, mixed-integer programming models, and applications for distribution system design.

TL;DR: The fundamental approaches for scheduling under uncertainty: reactive scheduling, stochastic project scheduling, fuzzy project Scheduling, robust (proactive) scheduling and sensitivity analysis are reviewed.

TL;DR: In this paper, the authors investigated the effect of data preprocessing, including deseasonalization and detrending, on neural network modeling and forecasting performance for seasonal time series forecasting.

TL;DR: In this paper, the authors extract the essence of SCM and advanced planning in the form of two conceptual frameworks: the house of supply chain management and the supply chain planning matrix.

TL;DR: The literature on executing production schedules in the presence of unforeseen disruptions on the shop floor is reviewed, and a taxonomy of the different types of uncertainty faced by scheduling algorithms is provided.

TL;DR: The many facets of this exciting and centrally placed field of facility siting are reviewed through reference to both seminal works and current reviews.

TL;DR: An aggregation process for dealing with non-homogeneous contexts, taking as base the 2-tuple fuzzy linguistic representation model, is developed and different extensions of this process are proposed to deal with contexts in which can appear other type of information as intuitionistic fuzzy sets or multi-granular linguistic information.

TL;DR: This paper presents a hybrid genetic algorithm for the job shop scheduling problem that is based on random keys and tested on a set of standard instances taken from the literature and compared with other approaches.

TL;DR: This method finds a solution to the corresponding VRP problem and modifies this solution to make it feasible for the VRPPD, and is capable of solving multi-depot problems, which has not been done before.

TL;DR: In this paper, the authors focus on the treatment of a company's most behaviorally loyal customers in a non-contractual setting and build a model in order to predict partial defection by behaviourally loyal clients using three classification techniques: Logistic regression, automatic relevance determination (ARD) Neural Networks and Random Forests.

TL;DR: It is shown that the optimal solution to a linear program that solves the mixed integer program has dual variables that have the traditional economic interpretation as prices, and can be used to interpret the solutions to nonconvex problems such as the problem discussed by Scarf.

TL;DR: A stochastic programming based approach by which a deterministic location model for product recovery network design may be extended to explicitly account for the uncertainties to give more insight into decision-making under uncertainty for reverse logistics.

TL;DR: Two kinds of mathematical programming formulations are proposed for some complex distribution network design problems, which involve facility location, warehousing, transportation and inventory decisions, and they are based on flow variables and constraints.

TL;DR: A new methodology for scheduling nurses in which several conflicting factors guide the decision process is presented, and results indicate that high-quality solutions can be obtained within a few minutes in the majority of cases.

TL;DR: This empirical study uses logit modelling to predict whether or not a purchase is made during the next visit to the website using both forward and backward variable-selection techniques, as well as Furnival and Wilson’s global score search algorithm to find the best subset of predictors.

TL;DR: Results of the study show that, if IEWS was effectively employed in bank supervision, it can be possible to avoid from the bank restructuring costs at a significant amount of rate in the long run.

TL;DR: This paper proposes a non-hierarchical, negotiation-based scheme which can be used to synchronize plans between two independent supply chain partners linked by material flows and shows how modified versions of these models can be utilized for evaluating material orders or supplies proposed by the supply chain partner and for generating counter-proposals.

TL;DR: The proposed fuzzy multiple attribute decision-making method is a generalised model, which can be applied to great variety of practical problems encountered in the naval architecture from propulsion/manoeuvring system selection to warship requirements definition.

TL;DR: This study presents an interval-parameter fuzzy two-stage stochastic programming (IFTSP) method for the planning of water-resources-management systems under uncertainty and demonstrates how the method efficiently produces stable solutions together with different risk levels of violating pre-established allocation criteria.

TL;DR: A survey of sensitivity analysis of simulation models can be found in this paper, where the authors survey classic and modern sensitivity analysis methods for experiments with simulation models, including group screening, Latin hypercube sampling (LHS), and space filling.

TL;DR: Computational outcomes indicate that the dual-channel strategy outperforms the other two channel strategies in most cases, and the cost reductions realized by the flexibility of theDual-channel system may be significant under some circumstances.

TL;DR: The objective of this paper is to show that justification is a simple technique that can be easily incorporated in diverse algorithms for the resource-constrained project scheduling problem––improving the quality of the schedules generated without generally requiring more computing time.

TL;DR: A dynamic programming-based heuristic to solve the scheduling problem and an algorithm to find lower bounds for benchmarking the schedules found by the heuristic are developed.

TL;DR: The two-phase hybrid metaheuristic was subjected to a comparative test on the basis of 356 problems from the literature with sizes varying from 100 to 1000 customers and the derived results show that the proposed two- phase approach is very competitive.

TL;DR: In this paper, the authors developed a multiered supply chain network model with both physical and electronic transactions and in which supply side risk as well as demand side risk are included in the formulation.

TL;DR: A comprehensive overview of the literature on inventory control models in which the demand rate of an item is a function of the initial inventory level and those in which it is dependent on the instantaneous inventory level is presented.

TL;DR: This paper will analyze the winner determination problem in case of multiple sourcing, and extend the concept of multi-attribute auctions to allow for configurable offers to provide suppliers with more flexibility in the specification of their bids.

TL;DR: The results obtained showed that the DEA models can provide robust estimates of cost efficiency even in situations of price uncertainty, and the applicability of the models developed is illustrated in the context of the analysis of bank branch performance.

TL;DR: A stylized model based on a recent antitrust ruling against Hill–Rom suggests that by taking back and reselling refurbished products, a manufacturer can increase both profit margins and sales––to the detriment of a non-interfering competitor.