The on-demand warehousing problem

Warehouses are key elements of supply chain networks, and great attention is paid to increase their efficiency. Highly volatile space requirements are enablers of innovative resource sharing concepts, where warehouse capacities are traded on online platforms. In this context, our paper introduces the on-demand warehousing problem from the perspective of platform providers. The objective prioritises demand–supply matching with maximisation of the number of transactions. If there is a tie, the secondary objective maximises the number of suppliers matched with at least one customer and the number of customers that have matches within a specific threshold with respect to the minimum achievable cost. Besides the mathematical integer programming formulation, a myopic list-based heuristic and an efficient matheuristic approach are presented and benchmarked against the performance of a commercial optimisation solver. The impact of several parameters on the platform's objective is analysed. A particularly relevant finding is that the pricing flexibility on the demand side does not necessarily imply higher payments to the supply side. All data instances are made available publicly to encourage more researchers to work on this timely and challenging topic

Validation and Performance Comparison of Two Scoring Systems Created Specifically to Predict the Risk of Deep Sternal Wound Infection after Bilateral Internal Thoracic Artery Grafting

Background: The Gatti and the bilateral internal mammary artery (BIMA) scores were created to predict the risk of deep sternal wound infection (DSWI) after bilateral internal thoracic artery (BITA) grafting. Methods: Both scores were evaluated retrospectively in two consecutive series of patients undergoing isolated multi-vessel coronary surgical procedures - i.e., the Trieste (n = 1,122; BITA use, 52.1%; rate of DSWI, 5.7%) and the Besan\ue7on cohort (n = 721; BITA use, 100%; rate of DSWI, 2.5%). Baseline patient characteristics were compared between the two validation samples. For each score, the accuracy of prediction and predictive power were assessed by the area under the receiver-operating characteristic curve (AUC) and the Goodman-Kruskal gamma coefficient, respectively. Results: There were significant differences between the two series in terms of age, gender, New York Heart Association functional class, chronic lung disease, left ventricular function, surgical priority, and the surgical techniques used. In the Trieste series, accuracy of prediction of the Gatti score for DSWI was higher than that of the BIMA score (AUC, 0.729 vs. 0.620, p = 0.0033). The difference was not significant, however, in the Besan\ue7on series (AUC, 0.845 vs. 0.853, p = 0.880) and when only BITA patients of the Trieste series were considered for analysis (AUC, 0.738 vs. 0.665, p = 0.157). In both series, predictive power was at least moderate for the Gatti score and low for the BIMA score. Conclusions: The Gatti and the BIMA scores seem to be useful for pre-operative evaluation of the risk of DSWI after BITA grafting. Further validation studies should be performed

Dynamic Collection Scheduling Using Remote Asset Monitoring: Case Study in the UK Charity Sector

Remote sensing technology is now coming onto the market in the waste collection sector. This technology allows waste and recycling receptacles to report their fill levels at regular intervals. This reporting enables collection schedules to be optimized dynamically to meet true servicing needs in a better way and so reduce transport costs and ensure that visits to clients are made in a timely fashion. This paper describes a real-life logistics problem faced by a leading UK charity that services its textile and book donation banks and its high street stores by using a common fleet of vehicles with various carrying capacities. Use of a common fleet gives rise to a vehicle routing problem in which visits to stores are on fixed days of the week with time window constraints and visits to banks (fitted with remote fill-monitoring technology) are made in a timely fashion so that the banks do not become full before collection. A tabu search algorithm was developed to provide vehicle routes for the next day of operation on the basis of the maximization of profit. A longer look-ahead period was not considered because donation rates to banks are highly variable. The algorithm included parameters that specified the minimum fill level (e.g., 50%) required to allow a visit to a bank and a penalty function used to encourage visits to banks that are becoming full. The results showed that the algorithm significantly reduced visits to banks and increased profit by up to 2.4%, with the best performance obtained when the donation rates were more variable

Integrating agri-environmental indicators, ecosystem services assessment, life cycle assessment and yield gap analysis to assess the environmental sustainability of agriculture

Agriculture's primary function is the production of food, feed, fibre and fuel for the fast-growing world population. However, it also affects human health and ecosystem integrity. Policymakers make policies in order to avoid harmful impacts. How to assess such policies is a challenge. In this paper, we propose a conceptual framework to help evaluate the impacts of agricultural policies on the environment. Our framework represents the global system as four subsystems and their interactions. These four components are the cells of a 2 by 2 matrix [Agriculture, Rest of the word]; [Socio-eco system, Ecological system]. We then developed a set of indicators for environmental issues and positioned these issues in the framework. To assess these issues, we used four well-known existing approaches: Life Cycle Assessment, Ecosystem Services Analysis, Yield Gap Analysis and Agro-Environmental Indicators. Using these four approaches together provided a more holistic view of the impacts of a given policy on the system. We then applied our framework on existing cover crop policies using an extensive literature survey and analysing the different environmental issues mobilised by the four assessment approaches. This demonstration case shows that our framework may be of help for a full systemic assessment. Despite their differences (aims, scales, standardization, data requirements, etc.), it is possible and profitable to use the four approaches together. This is a significant step forward, though more work is needed to produce a genuinely operational tool. © 2022 The Author

Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

International audienceA CO2-responsive land surface model (the ISBAA- gs model of M´et´eo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001–2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale

"You have to get wet to learn how to swim" applied to bridging the gap between research into personnel scheduling and its implementation in practice

Personnel scheduling problems have attracted research interests for several decades. They have been considerably changed over time, accommodating a variety of constraints related to legal and organisation requirements, part-time staff, flexible hours of staff, staff preferences, etc. This led to a myriad of approaches developed for solving personnel scheduling problems including optimisation, meta-heuristics, artificial intelligence, decision-support, and also hybrids of these approaches. However, this still does not imply that this research has a large impact on practice and that state-of-the art models and algorithms are widely in use in organisations. One can find a reasonably large number of software packages that aim to assist in personnel scheduling. A classification of this software based on its purpose will be proposed, accompanied with a discussion about the level of support that this software offers to schedulers. A general conclusion is that the available software, with some exceptions, does not benefit from the wealth of developed models and methods. The remaining of the paper will provide insights into some characteristics of real-world scheduling problems that, in the author’s opinion, have not been given a due attention in the personnel scheduling research community yet and which could contribute to the enhancement of the implementation of research results in practice. Concluding remarks are that in order to bridge the gap that still exists between research into personnel scheduling and practice, we need to engage more with schedulers in practice and also with software developers; one may say we need to get wet if we want to learn how to swim

Sources and Sinks of Greenhouse Gases from European Grasslands and Mitigation Options: The ‘GreenGrass’ Project

Adapting the management of grasslands may be used to enhance carbon sequestration into soil, but could also increase N2O and CH4 emissions. In support of the European post-Kyoto policy, the European \u27GreenGrass\u27 project (EC FP5, EVK2-CT2001-00105) has three main objectives: i) to reduce the large uncertainties concerning the estimates of CO2, N2O and CH4 fluxes to and from grassland plots under different climatic conditions and assess their global warming potential, ii) to measure net greenhouse gas (GHG) fluxes for different management which reflect potential mitigation options, iii) to construct a model of the controlling processes to quantify the net fluxes and to evaluate mitigation scenarios by up-scaling to a European level