Showing papers in "European Journal of Operational Research in 2011"

TL;DR: This paper systematically reviews the recent modeling developments for estimating the RUL and focuses on statistical data driven approaches which rely only on available past observed data and statistical models.

TL;DR: The OP is formally described and many relevant variants are presented and all published exact solution approaches and (meta) heuristics are discussed and compared.

TL;DR: This paper provides a literature review which categorizes the research to date on lateral transshipments, so that differences can be understood and gaps within the literature can be identified.

TL;DR: In this article, the impact of market price, marketing effort, and stocking quantity on customer demand, supplier prices can serve as a coordination mechanism in a supply chain setting, integrating alternative supplier pricing policies within the newsvendor framework, and how the buyer's risk profile moderates the news-vendor order quantity decision.

TL;DR: This paper discusses statistical properties and convergence of the Stochastic Dual Dynamic Programming method applied to multistage linear stochastic programming problems, and argues that the computational complexity of the corresponding SDDP algorithm is almost the same as in the risk neutral case.

TL;DR: Fuzzy Data Envelopment Analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs as discussed by the authors.

TL;DR: In this article, an enhanced version of the artificial bee colony heuristic was proposed to improve the solution quality of the original version, and the performance of the enhanced heuristic is evaluated on two sets of standard benchmark instances.

TL;DR: After an exhaustive computational and statistical analysis it can be concluded that the proposed method shows an excellent performance overcoming the rest of the evaluated methods in a comprehensive benchmark set of instances.

TL;DR: This paper surveys single-project, single-objective, deterministic project scheduling problems in which activities can be processed using a finite or infinite number of modes concerning resources of various categories and types.

TL;DR: A taxonomy and a review of this literature is presented, its contributions are cataloged, and opportunities for future research in this area are suggested.

TL;DR: This work develops a profit-maximizing optimization problem for determining optimal fleet size for a vehicle rental company and derives analytical results for its relationship to vehicle availability at each rental station in the company's network of locations.

TL;DR: The development of ORAHS as a platform for OR in health is reported on, and the papers presented at meetings over the 35Â years of its existence are analyzed.

TL;DR: The proposed algorithm, named Multi-Objective Differential Evolution Algorithm (MODEA) utilizes the advantages of Opposition-Based Learning for generating an initial population of potential candidates and the concept of random localization in mutation step to introduce a new selection mechanism for generating a well distributed Pareto optimal front.

TL;DR: A simple method, which combines the theorem of matrix multiplication, vectors dot product, and the definition of consistent pair-wise comparison matrix, to identify the inconsistent elements is proposed and the correctness of the proposed method is proved mathematically.

TL;DR: This model incorporates uncertainty in quality fractions on the optimal number of acquired cores by considering multiple quality classes and a multinomial quality distribution for an acquired lot and derives optimal acquisition and remanufacturing policies for both deterministic and uncertain demand.

TL;DR: It is shown how these families can be conveniently viewed within a common ejection chain framework which sheds light on their similarities and differences, and gives clues about the nature of potential enhancements to today's best methods that may provide additional gains in solving large and difficult TSPs.

TL;DR: The cost model can be used to select the single best supply point location from a discrete set of choices and how it can be embedded within existing location algorithms to choose multiple supply points.

TL;DR: A Monte-Carlo simulation-based algorithm is described that integrates a sample average approximation scheme with a Benders decomposition algorithm to solve problems having stochastic independent transportation costs.

TL;DR: This survey presents different graph clustering formulations, most of which based on graph cut and partitioning problems, and describes the main spectral clustering algorithms found in literature that solve these problems.

TL;DR: This paper considers vertical co-op advertising along with pricing decisions in a supply chain where demand is influenced by both price and advertisement and the feasibility of bargaining game is discussed in a bid to determine a scheme to share the extra joint profit.

TL;DR: The study shows that both supply chain strategy and risk-averse behavior have significant impacts on quality investment and pricing in a make-to-order supply chain with uncertain demand in international trade.

TL;DR: A bus network design problem for Tin Shui Wai, a suburban residential area in Hong Kong, is investigated, which considers the bus services from the origins inside this suburban area to the destinations in the urban areas, and the proposed integrated solution method, which can solve the route design and frequency setting problems simultaneously.

TL;DR: Bagging and boosting outperform other multi-classifier systems, and a new boosting algorithm, Error Trimmed Boosting, outperforms bagging and AdaBoost by a significant margin.

TL;DR: This paper attempts to shed light on trade-credit from a supplier's perspective, and presents it as a tool for supply chain coordination, and shows that the supplier's markdown allowance alone cannot fully coordinate the supply chain if the retailer employs direct financing.

TL;DR: In this article, the authors perform an extensive study of new and state-of-the-art space-filling sequential design methods, and show that the new sequential methods produce results comparable to the best one-shot experimental designs available right now.

TL;DR: This research develops a mathematical model using the multiple-allocation p-hub median approach that encompasses the dynamics of individual modes of transportation through transportation costs, modal connectivity costs, and fixed location costs under service time requirements.

TL;DR: An alternative network DEA model is constructed that embodies the internal structure for supply chain performance evaluation that takes the perspective of organization mechanism to deal with the complex interactions in supply chain.

TL;DR: In this paper, the authors classify the models in the literature based on the characteristics of the inventory system and review the proposed replenishment policies and discuss the available models and their performance.

TL;DR: This article shows that even though most ergonomic risk estimation methods involve nonlinear functions, they can be integrated into assembly line balancing techniques at low additional computational cost and indicates that re-balancing often leads to a substantial mitigation of ergonomic risks.

TL;DR: This paper presents mathematical models which cover specific aspects in the personnel scheduling literature and addresses complexity issues by identifying polynomial solvable and NP-hard special cases.