Adopting different wind-assisted ship propulsion technologies as fleet retrofit: An agent-based modeling approach

The maritime shipping industry will increasingly switch to low carbon fuels and adopt energy saving technologies (ESTs) to achieve the industry target of decarbonization. Among ESTs, deck equipment, including those based on wind propulsion technologies (WPTs), represents the largest potential fuel savings and a source of increasing innovation initiatives by industry actors. Previous contributions to WPT innovation have addressed barriers and drivers for increased adoption in the industry but failed to consider the specific aspects of the fleet retrofitting market. Through an agent-based simulation model, this work studies the effects of different policy and market scenarios (subsidies, fuel prices, and networking) on the adoption of WPT retrofitting solutions. The proposed model incorporates two decision steps for each vessel to adopt the technology (acquiring awareness of the technology, and a utility decision process to determine the WPT option). The study also expands on previous knowledge by modeling three WPT options and by integrating real world data of technology costs and their fuel savings as well as vessel features. Insights from simulations allow to identify the most convenient policies as well as the potential of alternative models to reduce introduction barriers (e.g., product-service business models).Interreg North Sea Region project WASP: Wind Assisted Ship Propulsion, "Run Wind Propulsion Technology real life trials on sea going ships in operation, showcase proven concepts, market adaptation, green sea transport" 38-2-6-19Spanish Ministry of Science, Andalusian GovernmentEuropean Commission RYC-2016-19800ERDF under CONFIA PID2021-122916NB-I00ERDF under SIMARK P18-TP-447

Sustainability in tourism determined by an asymmetric game with mobility

M.C. was supported by the Spanish Ministry of Science, Andalusian Government, University of Granada, and ERDF under grants SIMARK (P18-TP-4475) , RYC-2016-19800, and PPJIA2020-09 (TURCOMPLEX) . J.H. was supported by the University of Las Palmas de Gran Canaria, under grant COVID-19 04. M.P. was supported by the Slovenian Research Agency (Grant Nos. P1-0403 and J1-2457) . Funding for open access charge: Universidad de Granada/CBUA.Many countries worldwide rely on tourism for their economic well-being and development. But with issues such as over-tourism and environmental degradation looming large, there is a pressing need to determine a way forward in a sustainable and mutually rewarding manner. With this motivation, we here propose an asymmetric evolutionary game with mobility where local stakeholders and tourists can either cooperate or defect in a spatially structured setting. Our study reflects that sustainable tourism is primarily determined by an optimal trade-off between economic benefits of the stakeholders and their costs related to the application of sustainability policies. In contrast, the specific benefits and costs of the tourists are comparatively less relevant. The reader can also observe that allowing for greater tourist mobility decreases cooperation and leads to faster polarization among local stakeholders. In agreement with observations worldwide, we identify decreasing population densities in tourist areas in terms of both, stakeholders and tourists, to be a key aid to greater cooperation and overall sustainability of tourism. These results are rooted in spatial formations and complex alliances that manifest spontaneously through the evolutionary dynamics in a structured population.Spanish Ministry of Science, Andalusian Government, University of GranadaEuropean Commission P18-TP-4475 RYC-2016-19800 PPJIA2020-09University of Las Palmas de Gran Canaria COVID-19 04Slovenian Research Agency - Slovenia P1-0403 J1-2457Universidad de Granada/CBU

Car Sequencing Problem con flotas de vehículos especiales. Presentación

Car Sequencing Problem con demanda parcial incierta. Robustez en una multi-secuencia de vehículos mixtos.Partiendo del Car Sequencing Problem (CSP), introducimos el concepto demanda parcial incierta a través de la incorporación de Flotas de vehículos especiales en un plan de demanda. Tras resaltar las peculiaridades de una Flota y establecer las hipótesis de trabajo, proponemos un modelo de programación lineal entera mixta orientado a satisfacer el máximo número de restricciones CSP. Posteriormente, introducimos el concepto multi-secuencia de producción y proponemos funciones para medir su robustez. La versión robusta del CSP considera un conjunto de escenarios de la demanda para las Flotas y presenta funciones que miden el exceso sobre el requerimiento estándar de las opciones del CSP en planes de demanda, opciones concretas y ciclos de fabricación. Dichas funciones pueden emplearse como función objetivo en problemas de optimización y como métricas ante una muli-secuencia de producción concreta.Preprin

Evolution of cooperation and trust in an N-player social dilemma game with tags for migration decisions

S.D. would like to acknowledge the support of an Australian Government Research Training Program scholarship to study a PhD degree in Computer Science at the University of Newcastle, Australia, supervised by R.C.We present an evolutionary game model that integrates the concept of tags, trust and migration to study how trust in social and physical groups influence cooperation and migration decisions. All agents have a tag, and they gain or lose trust in other tags as they interact with other agents. This trust in different tags determines their trust in other players and groups. In contrast to other models in the literature, our model does not use tags to determine the cooperation/defection decisions of the agents, but rather their migration decisions. Agents decide whether to cooperate or defect based purely on social learning (i.e. imitation from others). Agents use information about tags and their trust in tags to determine how much they trust a particular group of agents and whether they want to migrate to that group. Comprehensive experiments show that the model can promote high levels of cooperation and trust under different game scenarios, and that curbing the migration decisions of agents can negatively impact both cooperation and trust in the system.We also observed that trust becomes scarce in the system as the diversity of tags increases. This work is one of the first to study the impact of tags on trust in the system and migration behaviour of the agents using evolutionary game theory.Australian GovernmentDepartment of Industry, Innovation and Scienc

The Role of the Tourism Network in the Coordination of Pandemic Control Measures

The emergence and spread of COVID-19 has severely impacted the tourism industry worldwide. In order to limit the effect of new pandemics or any unforeseen crisis, coordinated actions need to be adopted among tourism stakeholders. In this paper, we use an evolutionary game model to analyze the conditions that promote cooperation among different stakeholders in a tourism network to control high-risk crises. A data sample of 280 EU regions is used to define the tourism network of regions with a heterogeneous dependence on tourism. The results show that cooperation is helped by the existence of a structured tourism network. Moreover, cooperation is enhanced when coordination groups include small numbers of participants and when they are formed according to the similarity of tourism dependence.University of Las Palmas de Gran Canaria COVID-19-04Spanish GovernmentAndalusian GovernmentEuropean Commission P18-TP-4475 PID2021-122916NB-I00 RYC-2016-1980

Rewarding policies in an asymmetric game for sustainable tourism

Tourism is a growing sector worldwide, but many popular destinations are facing sustain- ability problems due to excessive tourist flows and inappropriate behavior. In these areas, there is an urgent need to apply mechanisms to stimulate sustainable practices. This paper studies the most efficient strategy to incentivize sustainable tourism by using an asymmet- ric evolutionary game. We analyze the application of rewarding policies to the asymmetric game where tourists and stakeholders interact in a spatial lattice, and where tourists can also migrate. The incentives of the rewarding policies have an economic budget which can be allocated to tourists, to stakeholders, or to both sub-populations. The results show that an adaptive rewarding strategy, where the incentive budget changes over time to one or the other sub-population, is more effective than simple rewarding strategies that are exclu- sively focused on one sub-population. However, when the population density in the game decreases, rewarding just tourists becomes the most effective strateg

Benefits of robust multiobjective optimization for flexible automotive assembly line balancing

“This is a pre-print of an article published inJ. Flex Serv Manuf. The final authenticated version is available online at: https://doi.org/10.1007/s10696-018-9309-y ” Chica, M., Bautista, J. & de Armas, J. Flex Serv Manuf J (2018). https://doi.org/10.1007/s10696-018-9309-yChanging conditions and variations in the demand are frequent in real industrial environments. Decision makers have to take into account this uncertainty and manage it properly. One clear example is the automotive industry where manufacturers have to assume an uncertain and heterogeneous demand. For instance, automotive manufacturers must adapt their decisions when balancing the assembly line by considering different flexible solutions. Our proposal is using robust multiobjective optimization and simulation techniques to provide managers with a set of robust and equally-preferred solutions for assembly line balancing. We study a Nissan case where the demand of each product family is uncertain. The problem is addressed by considering a robust multiobjective model for assembly line balancing based on a high number of production plans. After the selection of six different assembly line configurations, we study the implications of robustness metrics based on workstations’ overload. We show that the adverse managerial effects of not having flexible line configuration when demand changes are alleviated. For the real Nissan automotive case, our analysis and conclusions show the managerial and industrial benefits of using robust assembly lines. We also encourage decision makers to use robust multiobjective optimization methods for selecting the most flexible decisions.Peer ReviewedPostprint (author's final draft

Appendices for “Benefits of robust multiobjective optimization for flexible automotive assembly line balancing”

Postprint (published version

Evolutionary multiobjective optimization for automatic agent-based model calibration: A comparative study

This work was supported by the Spanish Agencia Estatal de Investigacion, the Andalusian Government, the University of Granada, and European Regional Development Funds (ERDF) under Grants EXASOCO (PGC2018-101216-B-I00), SIMARK (P18-TP-4475), and AIMAR (A-TIC-284-UGR18). Manuel Chica was also supported by the Ramon y Cajal program (RYC-2016-19800).The authors would like to thank the ``Centro de Servicios de Informática y Redes de Comunicaciones'' (CSIRC), University of Granada, for providing the computing resources (Alhambra supercomputer).Complex problems can be analyzed by using model simulation but its use is not straight-forward since modelers must carefully calibrate and validate their models before using them. This is specially relevant for models considering multiple outputs as its calibration requires handling different criteria jointly. This can be achieved using automated calibration and evolutionary multiobjective optimization methods which are the state of the art in multiobjective optimization as they can find a set of representative Pareto solutions under these restrictions and in a single run. However, selecting the best algorithm for performing automated calibration can be overwhelming. We propose to deal with this issue by conducting an exhaustive analysis of the performance of several evolutionary multiobjective optimization algorithms when calibrating several instances of an agent-based model for marketing with multiple outputs. We analyze the calibration results using multiobjective performance indicators and attainment surfaces, including a statistical test for studying the significance of the indicator values, and benchmarking their performance with respect to a classical mathematical method. The results of our experimentation reflect that those algorithms based on decomposition perform significantly better than the remaining methods in most instances. Besides, we also identify how different properties of the problem instances (i.e., the shape of the feasible region, the shape of the Pareto front, and the increased dimensionality) erode the behavior of the algorithms to different degrees.Spanish Agencia Estatal de InvestigacionAndalusian GovernmentUniversity of GranadaEuropean Commission PGC2018-101216-B-I00 P18-TP-4475 A-TIC-284-UGR18Spanish Government RYC-2016-1980

An Integrative Decision-Making Mechanism for Consumers’ Brand Selection using 2-Tuple Fuzzy Linguistic Perceptions and Decision Heuristics

Consumers perform decision-making (DM) processes to select their preferred brands during their entire consumer journeys. These DM processes are based on the multiple perceptions they have about the products available in the market they are aware of. These consumers usually perform different DM strategies and employ diverse heuristics depending on the nature of the purchase, ranging from more pure optimal choices to faster decisions. Therefore, the design of realistic DM approaches for modeling these consumer behaviors requires a good representation of consumer perceptions and a reliable process for integrating their corresponding heuristics. In this work, we use fuzzy linguistic information to represent consumer perceptions and propose four consumer DM heuristics to model the qualitative linguistic information for the consumer buying decision. In particular, we use 2-tuple fuzzy linguistic variables, which is a substantially more natural and realistic representation without falling in a loss of information. The set of selected heuristics differ in the degree of involvement the consumers give to their decisions. Additionally, we propose a heuristic selection mechanism to integrate the four heuristics in a single DM procedure by using a regulation parameter. Our experimental analysis shows that the combination of these heuristics in a portfolio manner improves the performance of our model with a realistic representation of consumer perceptions. The model’s outcome matches the expected behavior of the consumers in several real market scenarios