Exact Zoning Optimization Model for Marine Spatial Planning (MSP)

Marine spatial planning (MSP) has recently attracted more attention as an efficient decision support tool. MSP is a strategic and long-term process gathering multiple competing users of the ocean with the objective to simplify decisions regarding the sustainable use of marine resources. One of the challenges in MSP is to determine an optimal zone to locate a new activity while taking into account the locations of the other existing activities. Most approaches to spatial zoning are formulated as non-linear optimization models involving multiple objectives, which are usually solved using stochastic search algorithms, leading to sub-optimal solutions. In this paper, we propose to model the problem as a Multi-Objective Integer Linear Program. The model is developed for raster data and it aims at maximizing the interest of the area of the zone dedicated to the new activity while maximizing its spatial compactness. We study two resolution methods: first, a weighted-sum of the two objectives, and second, an interactive approach based on an improved augmented version of the ϵ-constraint method, AUGMECON2. To validate and study the model, we perform experiments on artificially generated data. Our experimental study shows that AUGMECON2 represents the most promising approach in terms of relevance and diversity of the solutions, compactness, and computation time.

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Quality tracing in meat supply chains

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2013.0308 ◽

2014 ◽

Vol 372 (2017) ◽

pp. 20130308 ◽

Cited By ~ 16

Author(s):

Miriam Mack ◽

Patrick Dittmer ◽

Marius Veigt ◽

Mehmet Kus ◽

Ulfert Nehmiz ◽

...

Keyword(s):

Supply Chains ◽

Process Analysis ◽

Decision Support Tool ◽

Temperature Monitoring ◽

Support Tool ◽

Logistics Network ◽

Primary Model ◽

Sensory Parameters ◽

And Storage

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

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Modeling and simulation of customer dissatisfaction, worker unpunctuality and tolerance to delay in make-to-order supply chains measured through customer lifetime value performance

Ingenieria y Universidad ◽

10.11144/javeriana.iyu22-2.mscd ◽

2018 ◽

Vol 22 (2) ◽

Author(s):

Jorge Andrés Alvarado Valencia ◽

Daniel Silva

Keyword(s):

Word Of Mouth ◽

Discrete Event ◽

Decision Support Tool ◽

Customer Lifetime Value ◽

Negative Word ◽

Support Tool ◽

Make To Order ◽

Customer Lifetime ◽

Lifetime Value

Introduction: We developed a model for a make-to-order supply chain to evaluate the effects of worker unpunctuality, tolerance to delay and word-of-mouth according to customer waiting time (dis)satisfaction in four customer lifetime value measures (CLTV): switching customers, the number of sales per customer, the average customer loyalty and the potential market reached. Methods: We developed a hybrid (agent-based and discrete-event) simulation in a 33 * 4 experimental design. Results: All of the variables were significant in the four CLTV measures, except for tolerance to delay. The positive word-of-mouth effect was greater than the negative word-of-mouth effect. There were significant interactions between positive and negative word-of-mouth. Conclusions: This type of model becomes a decision support tool for businesses to evaluate their mid-to-long term performance taking into account their customers’ long-term behaviors and the relationships between potential customers in repetitive and competitive environments.

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An online decision support tool to evaluate ecological weed management strategies

Weed Science ◽

10.1017/wsc.2019.21 ◽

2019 ◽

Vol 67 (4) ◽

pp. 463-473

Author(s):

Douglas Bessette ◽

Robyn Wilson ◽

Christian Beaudrie ◽

Clayton Schroeder

Keyword(s):

Decision Support ◽

Soil Quality ◽

Weed Management ◽

Decision Support Tool ◽

The United States ◽

Support Tool ◽

Organic Farmers ◽

Ecological Weed Management ◽

On Farm

AbstractWeeds remain the most commonly cited concern of organic farmers. Without the benefit of synthetic herbicides, organic farmers must rely on a host of ecological weed management (EWM) practices to control weeds. Despite EWM’s ability to improve soil quality, the perceived rate of integrated EWM strategy adoption remains low. This low adoption is likely a result of the complexity in designing and evaluating EWM strategies, the tendency for outreach to focus on the risks of EWM strategies rather than their benefits, and a lack of quantitative measures linking the performance of EWM strategies to farmers’ on-farm objectives and practices. Here we report on the development and deployment of an easy-to-use online decision support tool (DST) that aids organic farmers in identifying their on-farm objectives, characterizing the performance of their practices, and evaluating EWM strategies recommended by an expert advisory panel. Informed by the principles of structured decision making, the DST uses multiple choice tasks to help farmers evaluate the short- and long-term trade-offs of EWM strategies, while also focusing their attention on their most important objectives. We then invited organic farmers across the United States, in particular those whose email addresses were registered on the USDA’s Organic Research Integrity Database, to engage the DST online. Results show considerable movement in participants’ (n = 45) preferences from practices focused on reducing weeding costs and labor in the short term to EWM strategies focused on improving soil quality in the long term. Indeed, nearly half of those farmers (48%) who initially ranked a strategy composed of their current practices highest ultimately preferred a better-performing EWM strategy focused on eliminating the weed seedbank over 5 yr.

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Reduction of the long-term use of proton pump inhibitors by a patient-oriented electronic decision support tool (arriba-PPI): study protocol for a randomized controlled trial

Trials ◽

10.1186/s13063-019-3728-2 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Anja Rieckert ◽

Annette Becker ◽

Norbert Donner-Banzhof ◽

Annika Viniol ◽

Bettina Bücker ◽

...

Keyword(s):

Randomized Controlled Trial ◽

Decision Support ◽

Controlled Trial ◽

Decision Support Tool ◽

Routine Care ◽

Electronic Decision Support ◽

Support Tool ◽

Randomized Controlled ◽

Cluster Randomized

Abstract Background Proton pump inhibitors (PPIs) are increasingly being prescribed, although long-term use is associated with multiple side effects. Therefore, an electronic decision support tool with the aim of reducing the long-term use of PPIs in a shared decision-making process between general practitioners (GPs) and their patients has been developed. The developed tool is a module that can be added to the so-called arriba decision support tool, which is already used by GPs in Germany in routine care. In this large-scale cluster-randomized controlled trial we evaluate the effectiveness of this arriba-PPI tool. Methods The arriba-PPI tool is an electronic decision support system that supports shared decision-making and evidence-based decisions around the long-term use of PPIs at the point of care. The tool will be evaluated in a cluster-randomized controlled trial involving 210 GP practices and 3150 patients in Germany. GP practices will be asked to recruit 20 patients aged ≥ 18 years regularly taking PPIs for ≥ 6 months. After completion of patient recruitment, each GP practice with enrolled patients will be cluster-randomized. Intervention GP practices will get access to the software arriba-PPI, whereas control GPs will treat their patients as usual. After an observation period of six months, GP practices will be compared regarding the reduction of cumulated defined daily doses of PPI prescriptions per patient. Discussion Our principal hypothesis is that the application of the arriba-PPI tool can reduce PPI prescribing in primary care by at least 15% compared to conventional strategies used by GPs. A positive result implies the implementation of the arriba-PPI tool in routine care. Trial registration German Clinical Trials Register, DRKS00016364. Registered on 31 January 2019.

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Joint Optimization of Routes and Container Fleets to Design Sustainable Intermodal Chains in Chile

Sustainability ◽

10.3390/su12062221 ◽

2020 ◽

Vol 12 (6) ◽

pp. 2221

Author(s):

Alba Martínez-López ◽

Manuel Chica

Keyword(s):

Real Life ◽

Decision Support Tool ◽

Nsga Ii ◽

Policy Makers ◽

Support Tool ◽

Conflicting Objectives ◽

Objective Model ◽

Pareto Fronts ◽

Geographical Locations

This paper introduces a decision support tool for sustainable intermodal chains with seaborne transport, in which the optimization of a multi-objective model enables conflicting objectives to be handled simultaneously. Through the assessment of ‘door-to-door’ transport in terms of costs, time, and environmental impact, the most suitable maritime route and the optimized fleet are jointly calculated to maximize the opportunities for success of intermodal chains versus trucking. The resolution of the model through NSGA-II algorithms permits to obtain Pareto fronts that offer groups of optimized solutions. This is not only useful to make decisions in the short term, but also to establish long-term strategies through assessment of the frontiers’ behavior obtained when a sensitivity analysis is undertaken. Thus, consequences of transport policies on intermodal performance can be analyzed. A real-life case is studied to test the usefulness of the model. From the application case, not only the most suitable Motorway of the Seas with their optimized fleets are identified for Chile, but also significant general findings are provided for both policy makers and heads of ports to promote the intermodal option regardless of their geographical locations.

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Long-term prognostic counselling in people with multiple sclerosis using an online analytical processing tool

Multiple Sclerosis Journal ◽

10.1177/1352458520964774 ◽

2020 ◽

pp. 135245852096477

Author(s):

Ricardo Kosch ◽

Insa Schiffmann ◽

Martin Daumer ◽

Christian Lederer ◽

Antonio Scalfari ◽

...

Keyword(s):

Multiple Sclerosis ◽

Decision Support Tool ◽

Prognostic Information ◽

Web Based ◽

Online Tool ◽

Support Tool ◽

Expected Time ◽

Disability Status ◽

Analytical Processing

Background: Prognostic counselling is a sensitive issue in medicine and especially so in MS due to the highly heterogeneous disease course. However, people with MS (pwMS) seek prognostic information. The web-based ‘Evidence-Based Decision Support Tool in Multiple Sclerosis’ (EBDiMS) uses data of 717 patients from the London/Ontario cohort to calculate personalized long-term prognostic information. Objective: The aim of this study was to investigate the feasibility and effect of long-term prognostic counselling in pwMS using EBDiMS. Methods: Ninety consecutive pwMS were provided with personalized estimations of expected time to reach Expanded Disability Status Scale (EDSS) scores of 6 and 8 and time to conversion to secondary-progressive MS. Participants gave estimates on their own putative prognosis and rated the tool’s acceptability on six-step Likert-type scales. Results: Participants rated EBDiMS as highly understandable, interesting and relevant for patient–physician encounters, coping and therapy decisions. Although it provoked a certain degree of worry in some participants, 95% would recommend using the tool. Participants’ own prognosis estimates did not change significantly following EBDiMS. Conclusion: Long-term prognostic counselling using an online tool has been shown to be feasible in a clinical setting. EBDiMS provides pwMS with relevant, easy-to-understand, long-term prognostic information without causing relevant anxiety.

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Model-Based Decision Support Tools at Jugos S.A. Concentrated Fruit Juice Plant

INFORMS Journal on Applied Analytics ◽

10.1287/inte.2020.1045 ◽

2020 ◽

Vol 50 (4) ◽

pp. 255-268

Author(s):

Aníbal M. Blanco ◽

M. Susana Moreno ◽

Carolina Taraborelli ◽

Flavio D’Angelo ◽

Facundo Iturmendi ◽

...

Keyword(s):

Decision Support ◽

User Interfaces ◽

Decision Support Tool ◽

Raw Material ◽

Mixed Integer ◽

Support Tool ◽

Support Tools ◽

Optimal Target ◽

And Storage

We describe the development of a decision-support tool to assist in the operations of a large concentrated apple and pear juice plant. The tool’s objective is to generate detailed schedules of clarified juice batches to be produced in the following weeks considering incoming fruit forecasts, commercial commitments, and infrastructural constraints. The tool is based on two interactive modules, PLANNER and SIMOPT, with different and complementary purposes. Each module is based on mixed-integer models with specific inputs, outputs, and user interfaces. PLANNER consists of three submodules: (i) planning assigns a batch of concentrated juice to be produced on a specific day, taking into account cleaning activities, rest days, raw material availability, and production and storage constraints; (ii) preprocessing organizes juice orders in batches; and (iii) pooling provides a detailed monitoring of semielaborated juice in storage pools in terms of inventories and sugar and acid content. Finally, SIMOPT provides a detailed optimal operative condition of the plant together with a thorough calculation of specific costs. This information is used by PLANNER to evaluate the corresponding economic objective functions. Besides providing optimal target conditions to the plant and feasible production schedules, the developed tools generate production guidelines in the long term and allow performing scenario studies.

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A decision-support tool to assist muscle-invasive bladder cancer patients choosing between radical cystectomy and chemoradiotherapy.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.6_suppl.505 ◽

2018 ◽

Vol 36 (6_suppl) ◽

pp. 505-505

Author(s):

Brian Christopher Baumann ◽

Wei-Ting Hwang ◽

Sharadha Srinivasan ◽

Xingmei Wang ◽

Ronac Mamtani ◽

...

Keyword(s):

Bladder Cancer ◽

Decision Support ◽

Decision Support Tool ◽

Short Term ◽

Muscle Invasive Bladder Cancer ◽

Support Tool ◽

Trade Offs ◽

Muscle Invasive ◽

Break Even Point

505 Background: Patients with high-risk muscle-invasive bladder cancer (MIBC) who are borderline medically operable for radical cystectomy (RC) face a difficult decision between RC which has higher short-term treatment-related morbidity/mortality & chemoradiotherapy (CRT) which is better tolerated in the short-term but may have worse long-term cancer control outcomes. There are no existing decision support tools to assist patients & providers in understanding these trade-offs. Herein, we developed a visualization tool to inform patients & providers how the relative risks & benefits of RC & CRT vary over time with respect to overall survival (OS). Methods: We identified cT2-3 N0 M0 urothelial bladder cancer patients ≥65 y/o treated with RC +/- chemo (n = 5981) or definitive-dose CRT after TURBT (n = 793) in the National Cancer Database, 2003-2011. The database was split into a development & validation cohort. Multivariate Cox regression with time-varying hazard ratio was performed to assess pre-treatment factors associated with OS. The inverse probability of treatment weighting method using the propensity score was employed to reduce selection bias. External validation was performed. Visualization tool showing adjusted survival curves based on pre-op patient features was generated with input from patients & a multidisciplinary expert panel. Tool calculates median OS & the “break-even point,” where the short-term OS disadvantage of RC equals the long-term advantage of RC (i.e. the point where the restricted mean survival for RC & CRT are equal). Results: On MVA, significant predictors of OS were age, Charlson Deyo comorbidity index, & cT stage (p < 0.001 for all). Using these results, we iteratively developed a web application that utilizes clinical inputs to generate patient-specific survival curves that display estimated OS differences over time. Median OS, the break-even point, & percent alive at the break-even point are provided. Conclusions: This is the first decision-support tool developed to assist high-risk borderline operable MIBC patients & their providers in understanding the short-term & long-term trade-offs between RC & CRT. Additional testing is underway.

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An application of the use of safe minimum standards in the conservation of livestock biodiversity

Environment and Development Economics ◽

10.1017/s1355770x05002640 ◽

2006 ◽

Vol 11 (1) ◽

pp. 77-94 ◽

Cited By ~ 11

Author(s):

ADAM G. DRUCKER

Keyword(s):

Decision Support ◽

Sustainable Use ◽

Policy Decision ◽

Decision Support Tool ◽

Cost Ratio ◽

Support Tool ◽

Benefit Cost Ratio ◽

Livestock Sector ◽

Animal Genetic Resource ◽

Using Data

This paper adapts the safe minimum standard (SMS) approach so as to explore its use as a potential policy decision support tool that can be applied to issues related to the conservation and sustainable use of farm animal genetic resource (AnGR) diversity. Empirical SMS cost estimates are obtained using data from three AnGR economics case studies in Mexico and Italy. The findings support our hypothesis that the costs of implementing an SMS are low, both when compared with the size of subsidies currently being provided to the livestock sector (<1 percent of the total subsidy) and with regard to the benefits of conservation (benefit-cost ratio of >2.9).Nevertheless, despite providing a potentially useful AnGR conservation decision support tool, a critical assessment of the application reveals that a much more extensive quantification of the components required to determine SMS costs needs to be undertaken before this tool can be applied in practice.

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