Manuel Chica

• PhD Computer Science
• Senior Researcher at University of Granada

Reputation and punishment are significant guidelines for regulating individual behavior in human society, and those with a good reputation are more likely to be imitated by others. In addition, society imposes varying degrees of punishment for behaviors that harm the interests of groups with different reputations. However, conventional pairwise int...

Reputation and punishment are significant guidelines for regulating individual behavior in human society, and those with a good reputation are more likely to be imitated by others. In addition, society imposes varying degrees of punishment for behaviors that harm the interests of groups with different reputations. However, conventional pairwise int...

Although the maritime industry has introduced technological improvements, shipping activity is still a major contributor to greenhouse gas emissions. Using more intelligent incentive policies, such as subsidies, seems a way to increase green technology adoption. Our proposal is to engineer micro-level incentives to target a reduced set of adopters...

In social dilemmas, most interactions are transient and susceptible to restructuring, leading to continuous changes in social networks over time. Typically, agents assess the rewards of their current interactions and adjust their connections to optimize outcomes. In this paper, we introduce an adaptive network model in the snowdrift game to examine...

Polarization is common in politics and public opinion. It is believed to be shaped by media as well as ideologies, and often incited by misinformation. However, little is known about the microscopic dynamics behind polarization and the resulting social tensions. By coupling opinion formation with the strategy selection in different social dilemmas,...

Herding behavior has a social cost for individuals not following the herd, influencing human decision-making. This work proposes including a social cost derived from herding mentality into the payoffs of pairwise game interactions. We introduce a co-evolutionary asymmetric model with four individual strategies (cooperation vs. defection and herding...

Agent-based modeling has proven to be a useful simulation tool in marketing to analyze what-if scenarios and support strategic marketing decisions. Over the years, the field has evolved and there is a substantial number of scientific publications that focus on different aspects of agent-based modeling. However, there is no recent bibliometric analy...

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 initi...

Calibration is a crucial step for the validation of computational models and a challenging task to accomplish. Dynamic Energy Budget (DEB) theory has experienced an exponential rise in the number of published papers, which in large part has been made possible by the DEBtool toolbox. Multimodal evolutionary optimisation could provide DEBtool with ne...

In practical assembly enterprises, customization and rush orders lead to an uncertain demand environment. This situation requires managers and researchers to configure an assembly line that increases production efficiency and robustness. Hence, this work addresses cost-oriented mixed-model multimanned assembly line balancing under uncertain demand,...

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 stak...

Agent-based models establish a suitable simulation technique to recreate real complex systems, such as those approached in marketing. Reinforcement learning is about learning a behavior policy in order to maximize a long-term reward signal. In this work, we develop a deep reinforcement learning agent that represents a brand in an agent-based model...

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 t...

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 oth...

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 mobil...

The spread of COVID-19 and ensuing containment measures have accentuated the profound interdependence among nations or regions. This has been particularly evident in tourism, one of the sectors most affected by uncoordinated mobility restrictions. The impact of this interdependence on the tendency to adopt less or more restrictive measures is hard...

Opinion dynamics investigate the spreading and evolution of opinions among a set of individuals. This is especially relevant in decision-making —the process of selecting an alternative from a set of possible options—, that is commonly based on personal opinions which may evolve along time. In this work, we present a model of opinion dynamics where...

We present an evolutionary trust game to investigate the formation of trust in sharing economy situations, where participants have a fixed provider or consumer role, and can only choose between trustworthy or untrustworthy behaviour. There are a variety of sharing economy platforms catering for differing goods and services, the properties of which...

“Bee pollen” is pollen collected from flowers by honey bees. It is used by the bees to nourish themselves, mainly by providing royal jelly and brood food, but it is also used for human nutrition. For the latter purpose, it is collected at the hive entrance as pellets that the bees bring to the hive. Bee pollen has diverse bioactivities, and thus ha...

The spread of COVID-19 and ensuing containment measures have accentuated the profound interdependence among nations or regions. This has been particularly evident in tourism, one of the sectors most affected by uncoordinated mobility restrictions. The impact of this interdependence on the tendency to adopt less or more restrictive measures is hard...

This paper simulates the effect of the strategies implemented by politicians after the terrorists attacks in Madrid on 11 March 2004 on the ideological distance between voters and political parties. The attacks took place three days before the elections and changed the campaign’s agenda, which centered around the issue of who was responsible for th...

This paper presents a computational evolutionary game model to study and understand fraud dynamics in the consumption tax system. Players are cooperators if they correctly declare their value added tax (VAT), and are defectors otherwise. Each player's payoff is influenced by the amount evaded and the subjective probability of being inspected by tax...

Current dynamic markets require manufacturing industries to organize a robust plan to cope with uncertain demand planning. This work addresses the mixed-model multi-manned assembly line balancing under uncertain demand and aims to optimize the assembly line configuration by a robust mixed-integer linear programming (MILP) model and a robust solutio...

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 c...

Calibrating agent-based models involves estimating multiple parameter values. This can be performed automatically using automatic calibration but its success depends on the optimization method’s ability for exploring the parameter search space. This paper proposes to carry out this process using coral reefs optimization algorithms, a new branch of...

The joint optimization of production scheduling and maintenance planning has a significant influence on production continuity and machine reliability. However, limited research considers preventive maintenance (PM) and corrective maintenance (CM) in assembly permutation flow shop scheduling. This paper addresses the bi-objective joint optimization...

The current COVID-19 pandemic has impacted millions of people and the global economy. Tourism has been one the most affected economic sectors because of the mobility restrictions established by governments and uncoordinated actions from origin and destination regions. The coordination of restrictions and reopening policies could help control the sp...

Startup companies boost the quality of everyday life in almost all dimensions, and their products and services are of relevance everywhere. One of the most important goals that startups pursue is to increase the number of their users quickly. Users are of two types, new and returning. The present study presents an agent-based model to simultaneousl...

Purpose This paper aims to fill a gap in the existing literature by answering the following question: is the effect of envy on people's intention to share information the same in offline settings and on online social networks? Design/methodology/approach Two studies demonstrate (1) how envy that results from upward social comparisons affects peopl...

Recent large-scale migration flows from rural areas of the Mekong Delta (MKD) to larger cities in the South-East (SE) region of Vietnam have created the largest migration corridor in the country. This migration trend has further contributed to greater rural–urban disparities and widened the development gap between regions. In this study, our aim is...

This paper presents a computational evolutionary game model to study and understand fraud dynamics in the consumption tax system. Players are cooperators if they correctly declare their value added tax (VAT), and are defectors otherwise. Each player's payoff is influenced by the amount evaded and the subjective probability of being inspected by tax...

In the automotive and electronics industries, more than one operator work in the same workstation to assemble a high volume of products. When assigning the tasks of these products to workstations, we should fulfill the cycle time and precedence relationships. Limited research has investigated space restrictions to store tools or components (i.e., t...

Parameterization is one of the most challenging steps in the construction of individual-based models, and it is particularly relevant for the case of Dynamic Energy Budget (DEB) theory given that DEB parameters are mapped to a multimodal fitness landscape. This multimodal fitness landscape could correspond to parameterizations that provide the righ...

We study the impact of climate change induced migration on the evolution of cooperation using an N-player social dilemma game. Players in the population are divided into non-overlapped groups, and they can choose to either cooperate or defect within their group. At the same time, the players are mapped to the nodes of a scale-free network, enabling...

Marketers have an important asset if they effectively target social networks’ influentials. They can advertise products or services with free items or discounts to spread positive opinions to other consumers (i.e., word-of-mouth). However, main research on choosing the best influentials to target is single-objective and mainly focused on maximizing...

In this paper, we present an evolutionary trust game, taking punishment and protection into consideration, to investigate the formation of trust in the so-called sharing economy from a population perspective. This sharing economy trust model comprises four types of players: a trustworthy provider, an untrustworthy provider, a trustworthy consumer,...

Understanding consumer behaviors and how consumers react to marketing campaigns and viral word‐of‐mouth processes is crucial for marketers. Classical approaches try to infer this information from a global top‐down perspective. However, a more suitable and natural approach is to model consumer behaviors in a heterogeneous and decentralized bottom‐up...

The car sequencing problem is a well established problem that models the conflicts arising from scheduling cars into an assembly line. However, the existing approaches to this problem do not consider non-regular or out-of-catalog vehicles, which are commonly manufactured in assembly lines. In this paper, we propose a new problem definition that dea...

Artificial intelligence (AI) has proven to be useful in many applications from automating cars to providing customer service responses. However, though many firms want to take advantage of AI to improve marketing, they lack a process by which to execute a Marketing AI project. This article discusses the use of AI to provide support for marketing de...

Automated calibration methods are a common approach to agent-based model calibration as they can estimate those parameters which cannot be set because of the lack of information. The modeler requires to validate the model by checking the parameter values before the model can be used and this task is very challenging when the model considers two or...

In this paper, we use agent-based modeling (ABM) to study different obstacles to the expansion of contract rice farming in the context of Mekong Delta (MKD)'s rice supply chain. ABM is a bottom-up approach for modeling the dynamics of interactions among individuals and complex combinations of various factors (e.g., economic, social or environmental...

Migration is one of the many responses humans and societies make to ongoing demographic, economic, societal and environmental changes. In this work, we use agent-based modeling (ABM) to study the dynamics of migration flows across provinces and cities in the Mekong Delta, Vietnam. The strength of ABM is that it allows a bottom-up approach that focu...

Changing 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 the...

Resumen-Partiendo de los modelos TSALBP-ergo (Time and Space Assembly Line Balancing Problem with Ergonomic Risk), proponemos 9 métricas para medir la robustez de un equilibrado de línea según sus atributos temporales, espaciales y contingentes. La versión robusta de TSALBP-ergo considera diversos planes de demanda e incluye funciones que miden los...

Resumen-Car sequencing problem (CSP) es un problema tradicional de satisfacción de restricciones que refleja los problemas que surgen cuando una serie de vehículos se introducen en una cadena de producción. Sin embargo no considera vehículos no regulares o fuera de catálogo, pese a que en plantas reales pueden llegar a representar entre el 10 % y e...

Appendices for “Managerial and industrial benefits of using robust multiobjective optimization for balancing an automotive assembly line”

Image registration (IR) involves the transformation of different sets of image data having a shared content into a common coordinate system. To achieve this goal, the search for the optimal correspondence is usually treated as an optimization problem. The limitations of traditional IR methods have boomed the application of metaheuristic-based appro...

In medical imaging there is a special interest in relating information from different images frequently used for diagnosis or treatment. Image registration (IR) involves the transformation of different sets of image data having a shared content into a common coordinate system. The estimation of the optimal transformation is modelled either as a com...

The reliability estimation of engineered components is fundamental for many optimization policies in a production process. The main goal of this paper is to study how machine learning models can fit this reliability estimation function in comparison with traditional approaches (e.g., Weibull distribution). We use a supervised machine learning appro...

We investigate the effects of update rules on the dynamics of an evolutionary game-theoretic model - the N-player evolutionary trust game - consisting of three types of players: investors, trustworthy trustees, and untrustworthy trustees. Interactions between players are limited to local neighborhoods determined by predefined spatial or social netw...

We investigate the effects of update rules on the dynamics of an evolutionary game-theoretic model - the N-player evolutionary trust game - consisting of three types of players: investors, trustworthy trustees, and untrustworthy trustees. Interactions between players are limited to local neighborhoods determined by predefined spatial or social netw...

Trust and trustworthiness are of great importance in social and human systems, especially when considering managerial and economic decision-making. In this paper, we investigate the emergent dynamics of an evolutionary game-theoretic model – the N-player evolutionary trust game – consisting of three types of players: an investor, a trustee who is t...

We present a contract farming model in the context of rice supply chain in the Mekong Delta, Vietnam, with the use of agent-based simulation. The purpose of the simulation is to understand the motivation of farmers and contractors in their participation into the contract rice farming scheme. The decision-making process is based on two main factors:...

Marketers must constantly decide how to implement word-of-mouth (WOM) programs, and a well-developed decision support system (DSS) can provide them valuable assistance in doing so. The authors propose an agent-based framework that aggregates social network-level individual interactions to guide the construction of a successful DSS for WOM. The fram...

Freemium apps are creating new marketing scenarios, encouraging product adoption through customer-to-customer interaction. Agent-based models have become a useful tool for helping marketers to understand social dynamics in freemium apps. However, the parameters of these models need to be calibrated using real data in order to adjust its behaviour t...

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 má...

Marketers have to make decisions on how to implement word-of-mouth (WOM) programs and a well-developed decision support system (DSS) can provide them with valuable assistance. The authors propose an agent-based framework that aggregates social network-level individual interactions to guide the construction of a successful DSS for WOM. The framework...

Brands are one of the most important of a firm's assets. Brand-managing activities are typically related to brand positioning and integration with marketing campaigns, and can involve complex decisions. The branding of an organization is indeed a dynamic system with many cause-effect relationships as well as intangible and heterogeneous variables....

Brands are one of the most important of a firm's assets. Brand-managing activities are typically related to brand positioning and integration with marketing campaigns, and can involve complex decisions. The branding of an organization is indeed a dynamic system with many cause-effect relationships as well as intangible and heterogeneous variables....

Changes in demand when manufacturing different products require an optimization model that includes robustness in its definition and methods to deal with it. In this work we propose the r-TSALBP, a multiobjective model for assembly line balancing to search for the most robust line configurations when demand changes. The robust model definition cons...

Robust optimization tries to find flexible solutions when solving problems with uncertain scenarios and vague information. In this paper we present a multiobjective evolutionary algorithm to solve robust multiobjective ptimization problems. This algorithm is a novel adaptive method able to evolve separate populations of robust and non-robust soluti...

An appropriate visualization of multiobjective non-dominated solutions is a valuable asset for decision making. Although there are methods for visualizing the solutions in the design space, they do not provide any information about their relationship. In this work, we propose a novel methodology that allows the visualization of the non-dominated so...

We present a complete methodology for authenticating local bee pollen against fraudulent samples using image processing and machine learning techniques. The proposed standard methods do not need expensive equipment such as advanced microscopes and can be used for a preliminary fast rejection of unknown pollen types. The system is able to rapidly re...

In this contribution, we propose an interactive multicriteria optimisation framework for the time and space assembly line balancing problem. The framework allows decision maker interaction by means of reference points to obtain the most interesting non-dominated solutions. The principal components of the framework are the g -dominance preference sc...

System dynamics provides the means for modelling complex systems such as those required to analyse many economic and marketing phenomena. When tackling highly complex problems, modellers can soundly increase their understanding of these systems by automatically identifying the key variables that arise from the model structure. In this work we propo...

Partiendo de la familia de modelos TSALBP (Time and Space Assembly Line Balancing Problem), proponemos diversas funciones para medir la robustez de un equilibrado de línea atendiendo a sus atributos temporales y espaciales. La versión robusta de TSALBP considera un conjunto de escenarios de demanda y presenta funciones que miden el exceso de carga,...

Changes in demand when manufacturing different products require an optimization model that includes robustness in its definition and methods to deal with it. In this work we propose the r-TSALBP, a multiobjective model for assembly line balancing to search for the most robust line configurations when demand changes. The robust model definition cons...