Showing papers in "European Journal of Operational Research in 2020"

TL;DR: This study reviews more than two hundred papers on maintenance modeling and optimization that have appeared in the period 2001 to 2018, and distinguishes single-unit and multi-unit systems.

TL;DR: This study focuses on the e-tailer’s demand information sharing strategy with the supplier who may build upon brick-and-mortar stores and two extensions about consumer behavior in multichannel selection are discussed: showrooming and webrooming.

TL;DR: The analysis of a fashion supply chain consisting of one manufacturer and two competing retailers and how retail competition and consumer returns affect green product development in fashion apparel finds that the optimal greenness level of the fashion product decreases along with the level of market competition.

TL;DR: This paper focuses only on selection hyper-heuristics and presents critical discussion, current research trends and directions for future research, and the existing classification of selectionhyper- heuristics is extended, in order to reflect the nature of the challenges faced in contemporary research.

TL;DR: The mean-risk theory is applied to analytically explore how the risk attitude of customers affects the optimal service pricing decision of the on-demand platform, consumer surplus of customers, the expected profit and profit risk of the platform and the value of blockchain technology mediated customized service pricing strategy.

TL;DR: The objectives of this overview article are to motivate why researchers and practitioners from business analytics should utilize deep neural networks and review potential use cases, necessary requirements, and benefits, and investigate the added value to operations research in different case studies with real data from entrepreneurial undertakings.

TL;DR: A description of the basic principles of the hybrid metaheuristics is given, followed by a comparison of the results of the different hybrids on the well-known PSPLIB data instances.

TL;DR: Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest as mentioned in this paper, and the diversity of applications has motivated the study of a myriad of problem variants with different attributes.

TL;DR: This paper discusses the development of interdiction optimization models and algorithms, with an emphasis on mathematical programming techniques and future research challenges in the field, and examines contemporary interdictions problems involving incomplete information, information asymmetry, stochasticity and dynamic play.

TL;DR: A new and comprehensive minimum cost consensus model that considers distance to global opinion and consensus degree is presented and will be used to evaluate CRPs in which experts’ opinion evolution is considered to achieve an agreed solution for the GDM.

TL;DR: The results indicate that remanufacturing can effectively improve the level of carbon emission reduction and the profits of the manufacturer and the retailer.

TL;DR: A dynamic and data driven framework for predicting whether a customer is going to make purchase at the company within a certain time frame in the near future is established, and a new set of customer relevant features that derives from times and values of previous purchases are proposed.

TL;DR: Examination of strategic contracting between a monopoly platform and suppliers that sell their goods through the platform shows that asymmetric contracting, in which only the low-volume supplier adopts the agency contract, can arise in equilibrium.

TL;DR: This work develops an adaptive consensus model for the sub-groups composed of hybrid strategies, with or without a feedback mechanism, according to the different levels of inter and intra degrees of consensus.

TL;DR: This study analyzes the pricing competition in a dual-channel supply chain consisting of one capital-constrained supplier and one e-retailer providing finance and presents the value of e-Retailer finance and the impact of various financing, operational, and consumer-related factors on pricing and channel structure.

TL;DR: The subsidy policy offers the manufacturer greater incentives to abate pollution and yields higher profits for channel members; however, when emissions abatement is very costly and production emissions are highly damaging, the tax policy should be implemented, as the subsidy policy leads to lower social welfare and environmental performance.

TL;DR: The proposed model’s ability to consider vaccine coverage inequity is demonstrated and a derivative-free optimization approach is discussed, as an alternative solution method which can consider various different objective functions and constraints.

TL;DR: It is proved that the two-step inspection policy is less effective than the single-step one in this effect and suggested that the retailer's role in improving the distributor's non-cold chain transportation behavior should be fully used.

TL;DR: Two environmental subsidy policies are examined, namely, consumer and manufacturer subsidies, and it is found that the former yields a lower abatements and higher consumption quantity than the latter by focusing on consumption quantity instead of production emissions abatement.

TL;DR: The study identifies fourteen analytics-enabled micro-foundations of dynamic capabilities, essentially highlighting how organisations can use analytics to manage and enhance their OR activities in dynamic and uncertain environments.

TL;DR: The results suggest that Business Analytics directly improves environmental scanning which in turn helps to enhance a company's innovation and the pivotal roles of environmental scanning and data-driven culture.

TL;DR: A new selective maintenance optimization for multi-state systems that can execute multiple consecutive missions over a finite horizon is developed and a customized deep reinforcement learning method is put forth to overcome the “curse of dimensionality” and mitigate the uncountable state space.

TL;DR: This survey focuses on casualty management (CM), which is one of the actions taken in the response phase of a disaster, and categorizes the existing research papers and case studies in each of these steps to suggest future directions for academics and practitioners.

TL;DR: This study presents a bi-level optimization model to describe the interaction behaviors between decision makers and moderator, and develops the consensus mechanism with maximum-return modifications and minimum-cost feedback (MRMCCM).

TL;DR: There is a lack of papers that consider demand-side costs in their proposed model objectives; deal with uncertainty in funding, budget, asset and supply quantities, and infrastructure; considering prepositioning as a risk mitigation strategy; and use social media to better prepare for upcoming disasters.

TL;DR: The results suggest that predicting remanufactured product demand is a complex, non-linear problem, and that, by using advanced machine-learning techniques, the proposed approach can predict the product demand with high accuracy.

TL;DR: This paper reviews a variety of mathematical models for nesting problems under a common notation framework, allowing differences and similarities among them to be highlighted and research opportunities in the field to be proposed.

TL;DR: It is proved that IFPRs and the definitions of their additive consistency are special cases of those of LUPRs, and two types of consensus models developed based onLUPRs between the minimum deviation and belief degree are investigated.

TL;DR: A critical review of decision support frameworks—namely Portfolio Analysis, Multiple Criteria Decision Making and Fuzzy Cognitive Maps—is provided, and a new integrative approach, appropriately exploiting blends of these frameworks, is proposed to productively complement IAMs, towards enhancing climate policy support.

TL;DR: This paper associates to a pseudo-monotone variational inequality a forward-backward-forward dynamical system and carries out an asymptotic analysis for the generated trajectories and proves that linear convergence is guaranteed under strong pseudo- monotonicity.