JORS 是运筹学协会的官方期刊，发表原创研究论文，涵盖 OR 的理论、实践、历史或方法。

The Journal of the Operational Research Society is the official journal of the Operational Research Society, publishing original research papers that cover the theory, practice, history, and methodology of operational research.

《Journal of the Operational Research Society》是运筹学协会的官方期刊，发表原创研究论文，涵盖运筹学的理论、实践、历史和方法。

Journal of the Operational Research Society

Steel-making and continuous casting (SCC) processes are considered the main bottlenecks in the steel industry. We consider planning and scheduling problems in SCC processes and provide an overview of the literature with our commentary. The planning problem has as goal to create out of customer orders production units for the various production processes. The scheduling problem assigns these production units to the production facilities over different time intervals. We review a large number of planning and scheduling papers and propose two basic models for the planning and the scheduling problems that incorporate the most common and essential features. We describe for each problem the respective constraints and objectives as well as the practical implications in an actual production environment. We also analyse the methodologies used in their solutions, including decomposition strategies. In the last section, we present the conclusions of our survey and propose new research directions.

Myungho Lee

Kyungduk Moon

Kangbok Lee

Juntaek Hong

Michael Pinedo

A critical review of planning and scheduling in steel-making and continuous casting in the steel industry

钢铁工业中炼钢和连铸计划与调度的关键性综述

Design innovation is the engine of fashion. Many fashion firms outsource design innovation to their suppliers. Design outsourcing is on the rise in the fashion supply chain, but research in this area lags behind industry practice. In this paper, we examine how design outsourcing affects the supply chain, and we compare supply chain performance under an Original Equipment Manufacturer (OEM) strategy versus an Original Design Manufacturer (ODM) strategy. We evaluate a market size outsourcing model where design enhancement influences market size, and a success probability outsourcing model where design enhancement influences the success probability of innovation. We find that when the supplier trades with the retailer via a wholesale price contract under the ODM strategy, the supplier has no incentive to invest in innovation. In the market size outsourcing model, the design innovation in the centralized supply chain is higher than that under the OEM strategy. However, in the success probability outsourcing model, the success probability of innovation under the OEM strategy is higher than that in the centralized supply chain. Furthermore, we find that a profit sharing contract can achieve supply chain coordination under both OEM and ODM strategies; whereas, revenue sharing and buyback contracts cannot.

Bin Shen

Qingying Li

Ciwei Dong

Vincent Quan

Design outsourcing in the fashion supply chain: OEM<i>versus</i>ODM

时尚供应链中的设计外包：OEM与ODM之比较

Jatinder N. D. Gupta

Two-Stage, Hybrid Flowshop Scheduling Problem

两阶段混合流水车间调度问题

We propose new heuristic procedures for the maximally diverse grouping problem (MDGP). This NP-hard problem consists of forming maximally diverse groups—of equal or different size—from a given set of elements. The most general formulation, which we address, allows for the size of each group to fall within specified limits. The MDGP has applications in academics, such as creating diverse teams of students, or in training settings where it may be desired to create groups that are as diverse as possible. Search mechanisms, based on the tabu search methodology, are developed for the MDGP, including a strategic oscillation that enables search paths to cross a feasibility boundary. We evaluate construction and improvement mechanisms to configure a solution procedure that is then compared to state-of-the-art solvers for the MDGP. Extensive computational experiments with medium and large instances show the advantages of a solution method that includes strategic oscillation.

M Gallego

M Laguna

R Martí

A Duarte

Tabu search with strategic oscillation for the maximally diverse grouping problem

带有战略振荡的禁忌搜索用于最大多样化分组问题

Nowadays we are witnessing a transformation of the business processes towards a more computation driven approach. The ever increasing usage of Machine Learning techniques is the clearest example of such trend. This sort of revolution is often providing advantages, such as an increase in prediction accuracy and a reduced time to obtain the results. However, these methods present a major drawback: it is very difficult to understand on what grounds the algorithm took the decision. To address this issue we consider the LIME method. We give a general background on LIME then, we focus on the stability issue: employing the method repeated times, under the same conditions, may yield to different explanations. Two complementary indices are proposed, to measure LIME stability. It is important for the practitioner to be aware of the issue, as well as to have a tool for spotting it. Stability guarantees LIME explanations to be reliable, therefore a stability assessment, made through the proposed indices, is crucial. As a case study, we apply both Machine Learning and classical statistical techniques to Credit Risk data. We test LIME on the Machine Learning algorithm and check its stability. Eventually, we examine the goodness of the explanations returned.

Giorgio Visani

Enrico Bagli

Federico Chesani

Alessandro Poluzzi

Davide Capuzzo

Statistical stability indices for LIME: Obtaining reliable explanations for machine learning models

LIME的统计稳定性指数：获取机器学习模型的可靠解释

Benjamin Legros

How should rejection be used to maximize congestion while preserving idle time?

如何利用拒绝策略在保持空闲时间的同时最大化拥堵？

Burak Keskin

Joe Zhu

Anyu Yu

Performance analysis of sustainable development goals: a multi-component additive network DEA approach

可持续发展目标绩效分析：一种多组件加法网络DEA方法

Hui Feng

Renyan Mu

Lei Wu

Yirong Li

Balanced scheduling for medical waste treatment in public health emergencies via Simulation-Driven Mixed Integer Linear Programming

基于仿真驱动的混合整数线性规划的公共卫生紧急情况下医疗废物处理的平衡调度

Neonatal care for preterm and sick babies is organised into local areas around the United Kingdom, called Operational Delivery Networks. These networks coordinate between providers to ensure babies have the required care, close to home. There are three types of Neonatal Units offering distinct levels of needs-based care. The networks need to ensure that each unit operates at optimal cot levels, and the best quality care is provided. The possible impact of any changes to a network's configuration on transfers and infant care, must be considered before any changes are implemented. Our simulation model reflects the infant pathways within a network allowing users to evaluate a variety of possible changes within the network. The model builds on previous literature by incorporating the ability to move an existing infant from a unit to release capacity as well as moving new arrivals between units. We also consider the potential environmental impact of the additional travel for parents visiting infants who have been transferred. We demonstrate how the model can be applied with a case network within which approximately 60,000 babies are born annually, a tenth of whom requiring some Neonatal Care. Of these infants, approximately 12% are transferred to another unit.

Marion Penn

Joe Viana

Infant care transfers: simulating neonatal infant pathways and transfers across a neonatal network

婴儿护理转移：模拟新生儿在新生儿网络中的路径和转移

Over the past decade, the adoption of new digital technologies in healthcare has surged, significantly enhancing care delivery and accessibility. However, this digital transformation has been accompanied by a sharp increase in cyber-attacks, posing severe risks to hospital functionality and patient safety. To address the challenge of planning for uncertain future cyber incidents, we propose a two-stage stochastic model designed to bolster the cyber resilience of healthcare providers by selecting optimal countermeasures in preparation for upcoming cyber incidents. Numerical tests demonstrate the model's effectiveness, with the Value of the Stochastic Solution showing a 21% improvement over a deterministic approach. To be optimally equipped even for low-probability high-impact attacks we incorporate the risk measure Conditional Value-at-Risk. The corresponding countermeasure solution led to 44% fewer rejected patients in a worst-case scenario. The robustness of the proposed solution is underscored by its consistent performance across various scenarios, budget levels, and risk preferences, making it a reliable tool for enhancing cybersecurity in healthcare. These results highlight the importance of tailored, robust cybersecurity strategies in healthcare, ensuring preparedness for a wide range of potential threats.

Emilia Grass

Christina Pagel

Sonya Crowe

Saira Ghafur

A stochastic optimisation model to support cybersecurity within the UK national health service

支持英国国民医疗服务体系网络安全的随机优化模型

Abbreviation	J Oper Res Soc
Journal Impact	2.66
Quartiles(Global)	OPERATIONS RESEARCH & MANAGEMENT SCIENCE(Q2)

ISSN	0160-5682, 1476-9360
h-index	124

Publication Information	Publisher: Taylor and Francis Ltd.，Publishing cycle: Monthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1978，Proportion of original research papers: 98.69%，Self Citation Rate:14.80%， Gold OA Rate: 10.49%
Average review cycle	网友分享经验：平均7.0个月
Average recruitment ratio	网友分享经验：容易

Journal of the Operational Research Society

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