Letteratura scientifica selezionata sul tema "Choice modelling"

Discrete choice modelling can be employed to analyse tourists' holiday destination choices. The data for a destination choice modelling analysis are often obtained from a survey in which prospective tourists indicate their choices in a series of hypothetical scenarios. In that context, an issue deserving investigation is the use of destination names in the stated choice task. Using the names of destinations to label the alternatives in a choice scenario would be expected to enhance the predictive validity of the choice model. On the other hand, the experimental design of the choice scenarios may yield destination descriptions that appear unrealistic to survey respondents. In this paper, the labelling issue is investigated using a choice modelling study of short-break destination choices by residents from Melbourne, Australia. The multinomial logit model is used to compare the results of labelled and unlabelled stated choice tasks. The comparative results are reported and discussed and implications for destination choice modelling applications are drawn.

The production-constrained gravity formulation is shown to be an especially inaccurate specification of reality whenever the selection of destinations by individuals results from a hierarchical choice process. Hierarchical decisionmaking violates the Independence from Irrelevant Alternatives property embedded in the theoretical derivation of the production-constrained gravity model from choice axioms. Various aspects of gravity model misspecification resulting from hierarchical destination choice are investigated and an empirical example is given in terms of US migrants. A discussion is presented of several destination choice models that are more accurately specified than the gravity formulation when destination choice is hierarchical. The recently derived competing destinations formulation is shown to be amongst the most useful in this respect. The discussion is framed in the context of discrete choice theory.

Traditional decompositional preferences and choice studies are focused on the prediction of single choices, such as choice of shopping centre or transport mode. Discrete choice experiments are used to derive choice models that predict the probability of choosing a choice alternative as a function of its attributes. In this paper these traditional models are extended by addressing the problem of sequential choice behaviour. It is demonstrated how discrete choice experiments and universal logit models may be used to predict a choice sequence. The approach is illustrated for the problem of trip chaining. The research findings support the suggested approach.

Strategic planning is not only necessary in today's global economy where markets are becoming more susceptible to international competition, it is vital. The foresight of market reactions can lead to a competitive advantage. Market share losses can be minimized (and market share gains maximized) with the knowledge obtained from primary marketing research involving a stated preference study to examine consumer behaviour. Before launching a new product or providing a service, discrete choice analysis can empower strategic planners, managers and marketers with a tool which aids in optimizing products and services for a potential market with the end of maximizing sales and services.
Discrete choice analysis is a tool to understand human choice behaviour. It is employed for statistical inference on a model of choice behaviour from data obtained by sampling from a population of decision makers. This thesis gives an overview of the basic concepts of conjoint analysis which addresses discrete choice analysis for strategic product and service planning. The statistical model specification, the multinomial logit, is derived assuming that decision makers follow a choice rule called utility maximization, where these random utilities are Gumbel distributed. The model is applied to a stated preference study in which environmentally friendly vehicles are presented as possible vehicle choices.

This thesis contributes to the literature on the choice of transport mode for commuting trips, with special focus on the difference between urban and rural commuting in Scotland. The thesis begins by giving an overview of discrete choice theory and some empirical models consistent with this theory, before reviewing the literature on empirical applications of mode choice models for commuting trips. In the following, multinomial, nested and mixed logit models using data from a survey of commuters in the University of St Andrews are developed. The models are used to estimate aggregate mode-choice elasticities that can assist the development of efficient car reduction policies in St Andrews and other small towns in rural areas. The direct elasticities of the car mode are found to be comparable to estimates reported in studies of urban commuting, while the demand for public transport is found to be considerably more elastic. The value of in-vehicle travel time is found to be lower than in most studies of urban commuting, reflecting that the roads in the St Andrews area are relatively uncongested. Subsequently, current car drivers' willingness to use a Park and Ride service prior to the implementation of such a service are examined. The results show that the modal shift away from parking on-site will be small unless the new service is accompanied by measures aimed at making parking on-site less attractive such as introducing parking charges. Finally, the effect of the 'compact city' on modal split and congestion are examined. As well as making urban transport more sustainable as a result of an increase in the use of public transport, making cities more compact is found to contribute to lower levels of congestion in urban areas through a reduction in complex trip chains.

New Zealand is internationally renowned for having some of the finest and most challenging trout fishing in the world. However, due to continuing development and angling pressure many fishing sites are showing signs of environmental degradation and over fishing. This trend is almost certain to continue into the future given continued population and economic growth. Understanding the determinants of site choice, preference heterogeneity and anglers’ substitution patterns is fundamentally important to fishery managers who have the difficult task of maintaining quality angling experiences on a number of fishing sites, managing angling pressure and maintaining license sales. Recent advances in simulation techniques and computational power have improved the capability of discrete choice models to reveal preference heterogeneity and complex substitution patterns among individuals. This thesis applies and evaluates a number of state-of-the-art discrete choice models to study angler site choice in New Zealand. Recreation specialisation theory is integrated into the analysis to enhance the behavioural representation of the statistical models. A suite of models is presented throughout the empirical portion of this thesis. These models demonstrate different ways and degrees of explaining preference heterogeneity as well as identifying anglers’ substitution patterns. The results show that North Canterbury anglers’ preferences vary considerably. Resource disturbances such as riparian margin erosion, reduced water visibility and declines in catch rates can cause significant declines in angler use of affected sites, and at the same time non-proportional increases in the use of unaffected sites. Recreation specialisation is found to be closely related to the types of fishing site conditions, experiences and regulations preferred by anglers. Anglers’ preference intensities for fishing site attributes, such as catch rates, vary across different types of fishing sites. This location specific preference heterogeneity is found to be related to specialisation. Overall, the empirical findings indicate that conventional approaches to modelling angler site choice which do not incorporate a strong understanding of angler preference heterogeneity can lead to poorly representative models and suboptimal management and policy outcomes.

The worldwide market for organic foods is growing fast, but New Zealand meat producers have been slow to respond. Specifically, New Zealand producers have little or no organic lamb products for export or domestic sale. Part of the reason for this hesitancy to meet demand with supply is that the nature of the demand and consumer willingness to pay for the product is not well understood. The purpose of this study is to investigate New Zealand organic food consumers’ attitudes towards organic food and production methods and to evaluate consumer willingness to pay for an organic lamb product. Data for this study was collected using computer aided personal interviewing (CAPI) in supermarkets and speciality stores in Christchurch and Wellington. The study questioned consumers about their consumption habits, attitudes towards organic food and production methods and presented choice modelling scenarios to test willingness to pay for different attributes of lamb. Factor analysis is used to group the 12 attitudinal questions into three factors which were then placed into a two step cluster analysis to create consumer segments. Choice modelling was then used to measure consumer preferences for the tested attributes of lamb. From the factor and cluster analysis three distinct consumer segments were found and labelled as Committed Organic Seekers, Convenience Organic Consumers and Incidental Organic Consumers. These labels reflect each group’s organic consumption habits and attitudes towards organic food. The choice modelling results show that there is a willingness to pay for organic lamb. The three identified consumer groups state they would pay a premium of 61%, 44% and 26% respectively for organic lamb over standard pasture raised lamb. This paper gives an insight into consumer attitudes and preferences towards a product that could provide a way for New Zealand farmers to increase their returns. It contributes to the body of knowledge about the likely consumer profiles of regular consumers of organic food. There are only a few other studies that have attempted to measure consumer attitudes and willingness to pay for organic meat, however, the author is not aware of any published example of a study that has specifically investigated demand for organic lamb anywhere in the world. The study provides information about stated willingness to pay for five different attributes of lamb; this information should be of value in assisting the industry by showing which product offerings are likely to generate the highest sale price.

This thesis considers the evolution and the consequences of mate choice across a variety of taxa, using game theoretic, population genetic, and quantitative genetic modelling techniques. Part I is about the evolution of mate choice. In chapter 2, a population genetic model shows that mate choice is even beneficial in self-fertilising species such as Saccharomyces yeast. In chapter 3, a game theoretic model shows that female choice will be strongly dependent upon whether the benefits are fixed, so that females receive the same fitness boost from a mating with a given male regardless of how many matings that male has, or dilutable, where the more females a male mates with, the lower the expected benefit to each. This leads to the prediction that mating skew should be higher in species in which the benefits of mate choice are hypothesised to be due to good genes. Part II is about the consequences of mate choice. The theoretical prediction from chapter 3 is borne out by a literature review of studies of wild populations of birds in chapter 4. In chapter 5, a quantitative genetic model about poison-dart frogs suggests that sexual selection can speed up the effect of random genetic drift. This may be of more general importance, further widening the evolutionary impact of sexual selection. Finally, in chapter 6, a game theoretic model of sperm competition shows that pre-copulatory mate choice can also have evolutionary effects upon post-copulatory behaviour, affecting the optimal ejaculate expenditure of males. Overall, mate choice is shown to be an important evolutionary force, with wide-ranging ramifications across diverse taxa, and eects so varied as to include the evolution of sex, the genetic variation in species, speciation, and post-copulatory behaviour, amongst others. These effects can be effectively explored using mathematical modelling.

AbstractThis chapter is devoted to advanced issues of econometric modelling. The topics covered are, among others, models in willingness to pay space, the meaning of scale heterogeneity in discrete choice models and the application of various information processing rules such as random regret minimisation or attribute non-attendance. Other topics are anchoring and learning effects when respondents move through a sequence of choice tasks as well as different information processing strategies such as lexicographic preferences or choices based on elimination-by-aspects.

AbstractThis chapter addresses basic topics related to choice data analysis. It starts by describing the coding of attribute levels and choosing the functional form of the attributes in the utility function. Next, it focuses on econometric models with special attention devoted to the random parameter mixed logit model. In this context, the chapter compares different coefficient distributions to be used, addresses specifics of the cost attribute coefficient and it pays attention to potential correlations between random coefficients. Finally, topics related to the estimation procedure such as assuring its convergence or random draws are discussed.

We applied a 1-D plankton ecosystem-biogeochemical model to assess the impacts of ocean alkalinity enhancement (OAE) on seasonal changes in biogeochemistry and plankton dynamics. Depending on deployment scenarios, OAE should theoretically have variable effects on pH and seawater pCO2, which might in turn affect (a) plankton growth conditions and (b) the efficiency of carbon dioxide removal (CDR) via OAE. Thus, a major focus of our work is how different magnitudes and temporal frequencies of OAE might affect seasonal response patterns of net primary productivity (NPP), ecosystem functioning and biogeochemical cycling. With our study we aimed at identifying a parameterization of how magnitude and frequency of OAE affect net growth rates, so that these effects could be employed for Earth System Modell applications. So far we learned that a meaningful response parameterization has to resolve positive and negative anomalies that covary with temporal shifts. As to the intricacy of the response patterns, the derivation of such parameterization is work in progress. However, our study readily provides valuable insights to how OAE can alter plankton dynamics and biogeochemistry. Our modelling study first focuses at a local site where time series data are available (European Station for Time series in the Ocean Canary Islands ESTOC), including measurements of pH, concentrations of total alkalinity, dissolved inorganic carbon (DIC), chlorophyll-a and dissolved inorganic nitrogen (DIN). These observational data were made available by Andres Cianca (personal communication, PLOCAN, Spain), Melchor Gonzalez and Magdalena Santana Casiano (personal communication, Universidad de Las Palmas de Gran Canaria). The choice of this location was underpinned by the fact that the first OAE mesocosm experiment was conducted on the Canary Island Gran Canaria, which will facilitate synthesizing our modelling approach with experimental findings. For our simulations at the ESTOC site in the Subtropical North Atlantic we found distinct, non-linear responses of NPP to different temporal modes of alkalinity deployment. In particular, phytoplankton bloom patterns displayed pronounced temporal phase shifts and changes in their amplitude. Notably, our simulations suggest that OAE can have a slightly stimulating effect on NPP, which is however variable, depending on the magnitude of OAE and the temporal mode of alkalinity addition. Furthermore, we find that increasing alkalinity perturbations can lead to a shift in phytoplankton community composition (towards coccolithophores), which even persists after OAE has stopped. In terms of CDR, we found that a decrease in efficiency with increasing magnitude of alkalinity addition, as well as substantial differences related to the timing of addition. Altogether, our results suggest that annual OAE during the right season (i.e. physical and biological conditions), could be a reasonable compromise in terms of logistical feasibility, efficiency of CDR and side-effects on marine biota. With respect to transferability to global models, the complex, non-linear responses of biological processes to OAE identified in our simulations do not allow for simple parameterizations that can easily adapted. Dedicated future work is required to transfer the observed responses at small spatiotemporal scales to the coarser resolution of global models.

When testing an 1:N geotechnical structure in the centrifuge, it is desirable to choose a large scale factor (N) that can fit the small-scale model in a model container and avoid unwanted boundary effects, however, this in turn may cause scale effects when the structure is overscaled. This is more significant when it comes to small-scale modelling of sinker root-soil interaction, where root-particle size ratio is much lower. In this study the Distinct Element Method (DEM) is used to investigate this problem. The sinker root of a model root system under axial loading was analysed, with both upward and downward behaviour compared with the Finite Element Method (FEM), where the soil is modelled as a continuum in which case particle-size effects are not taken into consideration. Based on the scaling law, with the same prototype scale and particle size distribution, different scale factors/g-levels were applied to quantify effects of the ratio of root diameter (𝑑𝑟) to mean particle size (𝐷50) on the root rootsoil interaction.

This paper aims to estimate the future long-term care needs and expenditures in Quebec while proposing and evaluating a reform package that could deliver increased coverage as well as be more financially sustainable than current policy. This reform package consists of a shift towards more intensive use of home care while increasing public coverage of care needs. A key feature of the proposed reform is to improve the ability of users to choose their provider with the creation of a senior’s care account, an account that grants individuals in need to purchase services from several providers, including both home and institutional care. To improve the neutrality of public support across care arrangements, we also propose to increase residents’ contribution in nursing homes while favoring the continued use of existing tax credits to help seniors with lower needs in terms of care. Using detailed dynamic modelling of care needs, living arrangements, and expenditures, we estimate that long-term care needs will grow rapidly in the next two decades and the costs will quickly become prohibitive under current policy. We show that substantial cost savings may exist.

This paper aims to estimate the future long-term care needs and expenditures in Quebec while proposing and evaluating a reform package that could deliver increased coverage as well as be more financially sustainable than current policy. This reform package consists of a shift towards more intensive use of home care while increasing public coverage of care needs. A key feature of the proposed reform is to improve the ability of users to choose their provider with the creation of a senior’s care account, an account that grants individuals in need to purchase services from several providers, including both home and institutional care. To improve the neutrality of public support across care arrangements, we also propose to increase residents’ contribution in nursing homes while favoring the continued use of existing tax credits to help seniors with lower needs in terms of care. Using detailed dynamic modelling of care needs, living arrangements, and expenditures, we estimate that long-term care needs will grow rapidly in the next two decades and the costs will quickly become prohibitive under current policy. We show that substantial cost savings may exist.

Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asymptomatic disease in current (13%) and former (24%) Australian smokers.(4) The purpose of this Evidence Check review is to identify and analyse existing and emerging evidence for LDCT lung cancer screening in high-risk individuals to guide future program and policy planning. Evidence Check questions This review aimed to address the following questions: 1. What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? 2. What is the evidence of potential harms from lung cancer screening for higher-risk individuals? 3. What are the main components of recent major lung cancer screening programs or trials? 4. What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Summary of methods The authors searched the peer-reviewed literature across three databases (MEDLINE, PsycINFO and Embase) for existing systematic reviews and original studies published between 1 January 2009 and 8 August 2019. Fifteen systematic reviews (of which 8 were contemporary) and 64 original publications met the inclusion criteria set across the four questions. Key findings Question 1: What is the evidence for the effectiveness of lung cancer screening for higher-risk individuals? There is sufficient evidence from systematic reviews and meta-analyses of combined (pooled) data from screening trials (of high-risk individuals) to indicate that LDCT examination is clinically effective in reducing lung cancer mortality. In 2011, the landmark National Lung Cancer Screening Trial (NLST, a large-scale randomised controlled trial [RCT] conducted in the US) reported a 20% (95% CI 6.8% – 26.7%; P=0.004) relative reduction in mortality among long-term heavy smokers over three rounds of annual screening. High-risk eligibility criteria was defined as people aged 55–74 years with a smoking history of ≥30 pack-years (years in which a smoker has consumed 20-plus cigarettes each day) and, for former smokers, ≥30 pack-years and have quit within the past 15 years.(5) All-cause mortality was reduced by 6.7% (95% CI, 1.2% – 13.6%; P=0.02). Initial data from the second landmark RCT, the NEderlands-Leuvens Longkanker Screenings ONderzoek (known as the NELSON trial), have found an even greater reduction of 26% (95% CI, 9% – 41%) in lung cancer mortality, with full trial results yet to be published.(6, 7) Pooled analyses, including several smaller-scale European LDCT screening trials insufficiently powered in their own right, collectively demonstrate a statistically significant reduction in lung cancer mortality (RR 0.82, 95% CI 0.73–0.91).(8) Despite the reduction in all-cause mortality found in the NLST, pooled analyses of seven trials found no statistically significant difference in all-cause mortality (RR 0.95, 95% CI 0.90–1.00).(8) However, cancer-specific mortality is currently the most relevant outcome in cancer screening trials. These seven trials demonstrated a significantly greater proportion of early stage cancers in LDCT groups compared with controls (RR 2.08, 95% CI 1.43–3.03). Thus, when considering results across mortality outcomes and early stage cancers diagnosed, LDCT screening is considered to be clinically effective. Question 2: What is the evidence of potential harms from lung cancer screening for higher-risk individuals? The harms of LDCT lung cancer screening include false positive tests and the consequences of unnecessary invasive follow-up procedures for conditions that are eventually diagnosed as benign. While LDCT screening leads to an increased frequency of invasive procedures, it does not result in greater mortality soon after an invasive procedure (in trial settings when compared with the control arm).(8) Overdiagnosis, exposure to radiation, psychological distress and an impact on quality of life are other known harms. Systematic review evidence indicates the benefits of LDCT screening are likely to outweigh the harms. The potential harms are likely to be reduced as refinements are made to LDCT screening protocols through: i) the application of risk predication models (e.g. the PLCOm2012), which enable a more accurate selection of the high-risk population through the use of specific criteria (beyond age and smoking history); ii) the use of nodule management algorithms (e.g. Lung-RADS, PanCan), which assist in the diagnostic evaluation of screen-detected nodules and cancers (e.g. more precise volumetric assessment of nodules); and, iii) more judicious selection of patients for invasive procedures. Recent evidence suggests a positive LDCT result may transiently increase psychological distress but does not have long-term adverse effects on psychological distress or health-related quality of life (HRQoL). With regards to smoking cessation, there is no evidence to suggest screening participation invokes a false sense of assurance in smokers, nor a reduction in motivation to quit. The NELSON and Danish trials found no difference in smoking cessation rates between LDCT screening and control groups. Higher net cessation rates, compared with general population, suggest those who participate in screening trials may already be motivated to quit. Question 3: What are the main components of recent major lung cancer screening programs or trials? There are no systematic reviews that capture the main components of recent major lung cancer screening trials and programs. We extracted evidence from original studies and clinical guidance documents and organised this into key groups to form a concise set of components for potential implementation of a national lung cancer screening program in Australia: 1. Identifying the high-risk population: recruitment, eligibility, selection and referral 2. Educating the public, people at high risk and healthcare providers; this includes creating awareness of lung cancer, the benefits and harms of LDCT screening, and shared decision-making 3. Components necessary for health services to deliver a screening program: a. Planning phase: e.g. human resources to coordinate the program, electronic data systems that integrate medical records information and link to an established national registry b. Implementation phase: e.g. human and technological resources required to conduct LDCT examinations, interpretation of reports and communication of results to participants c. Monitoring and evaluation phase: e.g. monitoring outcomes across patients, radiological reporting, compliance with established standards and a quality assurance program 4. Data reporting and research, e.g. audit and feedback to multidisciplinary teams, reporting outcomes to enhance international research into LDCT screening 5. Incorporation of smoking cessation interventions, e.g. specific programs designed for LDCT screening or referral to existing community or hospital-based services that deliver cessation interventions. Most original studies are single-institution evaluations that contain descriptive data about the processes required to establish and implement a high-risk population-based screening program. Across all studies there is a consistent message as to the challenges and complexities of establishing LDCT screening programs to attract people at high risk who will receive the greatest benefits from participation. With regards to smoking cessation, evidence from one systematic review indicates the optimal strategy for incorporating smoking cessation interventions into a LDCT screening program is unclear. There is widespread agreement that LDCT screening attendance presents a ‘teachable moment’ for cessation advice, especially among those people who receive a positive scan result. Smoking cessation is an area of significant research investment; for instance, eight US-based clinical trials are now underway that aim to address how best to design and deliver cessation programs within large-scale LDCT screening programs.(9) Question 4: What is the cost-effectiveness of lung cancer screening programs (include studies of cost–utility)? Assessing the value or cost-effectiveness of LDCT screening involves a complex interplay of factors including data on effectiveness and costs, and institutional context. A key input is data about the effectiveness of potential and current screening programs with respect to case detection, and the likely outcomes of treating those cases sooner (in the presence of LDCT screening) as opposed to later (in the absence of LDCT screening). Evidence about the cost-effectiveness of LDCT screening programs has been summarised in two systematic reviews. We identified a further 13 studies—five modelling studies, one discrete choice experiment and seven articles—that used a variety of methods to assess cost-effectiveness. Three modelling studies indicated LDCT screening was cost-effective in the settings of the US and Europe. Two studies—one from Australia and one from New Zealand—reported LDCT screening would not be cost-effective using NLST-like protocols. We anticipate that, following the full publication of the NELSON trial, cost-effectiveness studies will likely be updated with new data that reduce uncertainty about factors that influence modelling outcomes, including the findings of indeterminate nodules. Gaps in the evidence There is a large and accessible body of evidence as to the effectiveness (Q1) and harms (Q2) of LDCT screening for lung cancer. Nevertheless, there are significant gaps in the evidence about the program components that are required to implement an effective LDCT screening program (Q3). Questions about LDCT screening acceptability and feasibility were not explicitly included in the scope. However, as the evidence is based primarily on US programs and UK pilot studies, the relevance to the local setting requires careful consideration. The Queensland Lung Cancer Screening Study provides feasibility data about clinical aspects of LDCT screening but little about program design. The International Lung Screening Trial is still in the recruitment phase and findings are not yet available for inclusion in this Evidence Check. The Australian Population Based Screening Framework was developed to “inform decision-makers on the key issues to be considered when assessing potential screening programs in Australia”.(10) As the Framework is specific to population-based, rather than high-risk, screening programs, there is a lack of clarity about transferability of criteria. However, the Framework criteria do stipulate that a screening program must be acceptable to “important subgroups such as target participants who are from culturally and linguistically diverse backgrounds, Aboriginal and Torres Strait Islander people, people from disadvantaged groups and people with a disability”.(10) An extensive search of the literature highlighted that there is very little information about the acceptability of LDCT screening to these population groups in Australia. Yet they are part of the high-risk population.(10) There are also considerable gaps in the evidence about the cost-effectiveness of LDCT screening in different settings, including Australia. The evidence base in this area is rapidly evolving and is likely to include new data from the NELSON trial and incorporate data about the costs of targeted- and immuno-therapies as these treatments become more widely available in Australia.

Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form. The output non-linearities can be approximated using a quadratic model, which creates a problem in the linear-quadratic framework. This facilitates the direct application of linear control approaches such as LQR control, predictive control, or Model Predictive Control (MPC). The paper demonstrates the approach using the ELectrified Vehicle library for sImulation and Optimization (ELVIO). It is an open-source MATLAB/Simulink library designed for the quick and easy simulation and optimization of different powertrain and drivetrain architectures. It follows a modelling methodology that combines backward-facing and forward-facing signal path, which means that no driver model is required. The results show that the approximated solution provides a performance that is very close to the solution of the original problem except for extreme parts of the operating range (in which case the solution tends to be driven by constraints anyway).