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Special SessionsMetaheuristics for industry 4.0Organized by:BENCHEIKH Ghita, LINEACT-Engineering School Cesi, France. FocusThe fourth industrial revolution, also known as Industry 4.0, has brought major changes in the way industries think and operate, with the integration of advanced technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI) and machine learning (ML). These technologies enable the collection, processing, and analysis of large amounts of data, which allows predicting incoming events, identifying areas for improvement, anticipating potential dangers, and improving efficiency, productivity, and decision-making. Metaheuristics are optimization algorithms that have proven their effectiveness in solving complex industrial problems. However, the adaptation of metaheuristics to Industry 4.0 technologies has not yet been widely explored, despite the potential benefits this could bring to industrial processes. By successfully adapting metaheuristics to Industry 4.0 technologies, we can contribute to the continued development of advanced industrial optimization methods and facilitate the adoption of Industry 4.0 in various industries. The objective of this special session is to study the adaptation of metaheuristics to Industry 4.0 technologies, with the aim of improving the effectiveness and efficiency of industrial processes. Specifically, we will focus on the design of adapted metaheuristics that receive real-time data from IoT sensors and use AI techniques to improve metaheuristic algorithms. In this context, this special session focuses on the study of new metaheuristics compatible with Industry 4.0 technologies. Therefore, this special session aims to discuss recent advances and developments in this area. The special session will be an excellent opportunity to exchange knowledge and promote collaboration between experts in the field. Topics under this session include (but not limited to)
Multi-agent systems for solving combinatorial optimization problemsOrganized by:BENCHEIKH Ghita, LINEACT-Engineering School Cesi, France. FocusCombinatorial optimization problems (COPs) are complex problems that involve finding the best solution among a large number of feasible solutions. These problems are found in various domains, including logistics and operations management, where optimal solutions for routing, scheduling, and allocation problems must be found. Solving COPs is a challenging task due to the size of the search area and the need to provide high quality solutions in a reasonable computing time. To address these challenges, researchers have investigated different solution strategies, including diversification techniques to escape from local optima. Decomposition of complex problems into several smaller, manageable sub problems is one of the arising approaches that cope with the increasing complexity encountered in challenging optimization problems. Inspired by the concept of "divide and conquer", it consists of decomposing a whole problem into smaller sub problems and optimizing them in a distributed manner to find high-quality solutions for the original problem. The use of multi-agent systems is one of the promising ways to implement this approach. By coordinating their actions and exchanging information, the agents can collectively achieve common goals. In addition, the use of AI, machine learning, and formal method based techniques can also make the search strategy more intelligent and informative. These techniques can be used to develop new generic approaches that can be applied to a wide range of COPs. In this context, this special session focuses on investigating new strategies for dealing with COPs. The session will bring together researchers and practitioners working on COPs, multi-agent systems and optimization problems to share ideas and discuss new approaches. The special session will be an excellent opportunity to exchange knowledge and promote collaboration among experts in the field. Topics under this session include (but not limited to)
Decarbonizing Short Food Supply ChainsOrganized by:
FocusShort Food Supply Chains (SFSCs) are emerging as a possible solution to inflation, which is primarily due to the increase in energy prices. The session aims to address the arbitrary choices consumers face when deciding between SFSCs and conventional supply chains, considering their implications and effectiveness in mitigating the impacts of inflation. Additionally, the session will explore how decarbonization of transport can enhance the sustainability and efficiency of SFSCs, by decreasing energy consumption and environmental impact. We seek to foster insightful conversations and innovative approaches to tackle the challenges posed by energy prices volatility while promoting localized and resilient food systems. Academic researchers and professionals are encouraged to submit papers incorporating optimization modelling, statistical and econometric modelling and other quantitative approaches. Models and Algorithms for electric mobilityOrganized by:
FocusThe transition to electric mobility has received significant attention in recent years, as societies around the world address the pressing challenges of climate change, air pollution and fossil fuel dependency. To investigate the multiple aspects of electric mobility, this special session invites the submission of original research papers focusing on modeling, optimization, simulation, and decision-making methods adapted to the field of electric mobility. We particularly encourage contributions that address uncertainty, and/or robustness, and/or resilience. The aim of this session is to disseminate recent theoretical and methodological advances, significant technical applications, case studies and survey results related to modeling, simulation, optimization, and artificial intelligence (AI) in the context of electric mobility. We welcome contributions that explore new approaches to electric vehicle dynamics modeling, charging infrastructure optimization, energy management systems, intelligent transportation systems and AI-based decision-making algorithms for electric mobility. Papers highlighting the wider implications of electric mobility, such as environmental sustainability, energy efficiency, economic viability and social acceptance are welcome. Topics under this session include (but are not limited to)
Sustainability in Supply Chain Management: A Paradigm for Global TransformationOrganized by:Fatima Zahra Mhada: ENSIAS, Mohammed V University, Morocco FocusMore and more companies recognize the importance of the concept of the sustainable supply chain to address environmental, social and economic challenges. The traditional supply chain prioritized profitability and often neglecting its impact on the environment and society. However, with growing concerns about climate change, resource depletion and social equity, businesses are now being forced to adopt a sustainable approach to remain competitive. Sustainable supply chain management integrates environmental, social and economic considerations throughout the supply chain life cycle. This involves rethinking its sourcing, production, logistics and end-of-life product management processes to reduce waste, minimize carbon footprint, promote fair practices, foster innovation, improve operational efficiency, mitigate risk and improve their reputation and brand image. This special session aims to present a comprehensive overview and understanding of sustainable supply chain management (SSCM) and its role in achieving a more sustainable future. Topics under this session include (but not limited to)
Sustainable and Agile Supply Chain ManagementOrganized by:
FocusSupply chain management constantly faces many challenges and one of them is to operate in an agile and sustainable manner. This special session mirrors the increasing relevance of this topic for both practitioners and academics. Hence, environmental and social considerations and challenges do not stop at the gates of single companies, but have to be considered along the supply chain, from a wider perspective. Papers interested in exploring the issue of sustainability in supply chain management, in addition to economic and cost factors are welcome in this special session. Topics include but are not limited to:
Lean and Analytical Approaches in Urban Logistics and Supply Chain 4.0Organized by:
FocusEfficiency and sustainability in modern urban environments heavily rely on the vital functions of logistics and supply chain management. Strategic facility placement and effective logistics operations management are indispensable for meeting increasing customer demands while mitigating environmental consequences. Hence, it is imperative to investigate the progress of lean and analytical techniques implemented in urban logistics and prioritize the delicate equilibrium between efficiency and sustainability. By examining fundamental concepts, addressing challenges, and proposing solutions, we can acquire valuable knowledge about how analytical methods can foster the development of a more sustainable and efficient urban and industrial system. While efficiency is important for the success of operation management within urban space, achieving sustainability goals is equally crucial in facility location decisions. Sustainable facility location seeks to minimize negative environmental, social, and economic impacts while maximizing long term benefits. Particularly, aspects related to the movement of goods and services within the urban areas. Therefore, sustainable urban logistics aims to rethink the design of transportation networks, optimize routing and scheduling, and promote alternative modes of transport. The objective of this special session is to explore the synergy between urban logistics and operations management under the scope of sustainability and resilience. Especially, we will focus on the use of analytical methods in supporting the integrated decision-making such as simulation models and optimization algorithms to support the assessments of diffident elements such as transportation, land use, energy consumption, automation, and environmental quality. Target topics relevant to this special session include but not limited to:
Artificial Intelligence and Emerging Technologies: Advancements and ApplicationsOrganized by:Ahmed EL HILALI ALAOUI, Euro-Mediterranean University of Fes, Morocco. FocusThis conference session at GOL'24 will focus on the latest advancements in artificial intelligence and emerging technologies. We will examine the latest innovations in robotics, collaborative robotics (cobots), logistics systems modeling, decision support systems, information systems, and machine learning. The objective of this session is to showcase the latest innovations and opportunities presented by these technologies across various sectors. Researchers and professionals are encouraged to submit papers highlighting the latest developments and practical applications of artificial intelligence and emerging technologies. Artificial Intelligence Techniques and Statistical modeling for Mobility and urban logistics planningOrganized by:
FocusMobility and urban logistics are fundamental components that contribute to a country's overall development and closely intertwine with societal transformations. They play a crucial role in achieving genuine sustainable development but also present significant challenges, particularly in developing and emerging nations. The effective management and planning of mobility and urban logistics are of utmost importance in addressing the pressing issues and intricacies associated with transportation. This includes ensuring the seamless functioning of cities, facilitating efficient transportation systems, and fostering sustainable growth. In this special session, our focus is on exploring the latest trends and advancements in mobility and urban planning approaches. We particularly encourage research papers that delve into the utilization of cutting-edge techniques such as machine learning, deep learning, discrete choice modeling, data meaning, and cloud-based approaches. By examining these innovative methods, we aim to gain insights into their applications, benefits, and potential impact on enhancing mobility and urban planning strategies. Artificial Intelligence Enhanced Urban LogisticsOrganized by:
FocusThe integration of urban delivery systems, machine learning/artificial intelligence (AI), and last-mile delivery offers numerous benefits in improving urban delivery systems' efficiency, dependability, and sustainability. There has been significant attention on analyzing diverse data sources, such as historical order records, weather conditions, and local events, to anticipate demand and delivery patterns, considering traffic congestion. Leveraging this information makes optimizing delivery schedules and allocating resources possible, reducing delivery times, fuel consumption, and greenhouse gas emissions. An area attracting increasing interest is Automated Vehicle Dispatching Systems, which facilitate real-time delivery task assignment to available vehicles. These systems minimize delays and idle time by considering traffic congestion, delivery time windows, and unused vehicle capacities. Crowdsourcing also appears as a viable alternative. Enhanced matching and auction systems allow companies to reach external resources on the fly for handling and delivering. Fleet Management and Maintenance systems also utilize vehicle monitoring and predictive maintenance techniques to identify potential issues. They optimize maintenance schedules and minimize downtime. In the growing transport electrification, charge management and autonomy estimation will be crucial in pick-and-delivery operations. Recent developments in Autonomous Delivery Systems enable robotic vehicles to navigate urban environments, ensuring efficient and secure deliveries. Another noteworthy aspect is Customer Delivery Personalization, which utilizes delivery data to predict preferred schedules and provide real-time updates, enhancing customer satisfaction. In reverse logistics, there is a growing interest in Return Prediction Systems. These systems help identify the volume of returned products and determine the optimal placement of return centers. To streamline the decision-making process, Automatic Waste Assessment & Classification Systems can be employed to determine whether returned items should be repaired, refurbished, or appropriately disposed of. A specific case involves an inventory of limited high-value waste materials. Topics under this session include (but are not limited to)
The contributions of Artificial Intelligence to Embedded Systems : Recent technological developmentsOrganized by:
FocusEmbedded systems (ES) are one of the fastest-growing fields. It incomporate computer software and hardware components in order to perform specific operations within a more significant technological system. For this purpose, constant pressure for innovations and advancements prevails to pick up new reliable and efficient overall results. Recent technological developments in artificial intelligence (AI), edge computing, sensors, and connectivity have accelerated the integration of data analysis based on embedded AI capabilities, that merge embedded machine learning and deep learning based on neural networks architectures, into resource-constrained, energy-efficient hardware devices for processing information at the network edge. This allows the reduction of costs, processing time and communication by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. Through this special session, we aim to focus on the context of modern embedded vision systems, witch explore the benefits of AI technologies in ES. This is to provide an overview of the latest research outcomes, developments and activities in technologies and applications of embedded AI. Researchers and professionals are encouraged to submit papers highlighting recent research on embedded AI dealing with methodologies, tools, and techniques to present insight into technological innovations and their industrial use. Sustainable and Smart Management of Water resources : Innovative Optimization solutionsOrganized by:
FocusLimited water resources, hydrological cycle affected by climate change, increasing demand and rapid urbanization in recent decades, have forced humanity to think of manners to combat this trend, and poses great challenges to three main factors of water resources allocation : efficiency, equity and sustainability. Thus, the optimization of water resources as well as sustainable development and optimal use, present one of the best ways for the preservation of these natural resources. The water resources planning and management is the process which promotes the coordinated monitoring and development of water and related resources. The main objectif is to maximize in an equitable way the social and economic resultant, while maintaining the vital ecosystems sustainability. Therefore, the use of appropriate and innovative optimization techniques can be helpful and efficient in this regard. Sunstainable and smart water management is the activity of planning, managing and developing the use of water resources based on Big Data and Artificial Intelligence technologies, in order to make more sustainable and reasonable usage of these water resources. Wich can provide to utility operators of water, the capability to measure and control their water consumption and networks distribution as well as the quantity and quality of the distributed water. Through this special session, we aim to focus on the context of sustainable management of water resources as a vital part of sustainable development. Researchers and professionals are encouraged to submit papers highlighting latest and recent research and innovative solutions for present as well as future challenges of the sustainable and smart water monitoring systems. Intelligent Approaches for Effective Intermodal Operations ManagementOrganized by:
FocusTo ensure the efficient and effective operation of the intermodal transport chain, intelligent approaches such as Machine learning (ML), Reinforcement Learning (RL), and Multi-Agent Systems (MAS) can be utilized. These intelligent techniques can contribute to optimizing various aspects of the intermodal chain, including the configuration of the transport network, mode selection, intermodal terminal choices, and equipment management. AI-based algorithms can analyze complex data sets and provide valuable insights for making informed decisions regarding transport planning and operations scheduling. They can be employed to optimize, among others, handling and transport operations within terminals, and the selection of transport modes and intermodal terminals based on historical data and performance evaluations. They can also facilitate coordination and collaboration among multiple agents within the transport chain, enabling real-time information sharing and decision-making to enhance overall performance. By incorporating intelligent approaches, the intermodal transport chain can achieve several benefits. Reducing travel time and cost of storage and transshipment can enhance the competitiveness of multimodal transportation. Additionally, intelligent planning can improve resource utilization, minimize delays, and increase the chances of achieving economies of scale. Therefore, the application of ML, RL, MAS, and other intelligent approaches is essential in ensuring the efficient and effective operation of the intermodal transport chain, leading to improved overall performance and enhanced competitiveness in the transport sector. Ecomobility & Freight transportOrganized by:
FocusEcomobility promotes ecological and sustainable transport. First and foremost, Ecomobility requires a long-term shift towards decarbonization, in order to gradually reduce greenhouse gas emissions while developing alternative energies. In the short term, travel and infrastructure must be optimized to reduce pollution and other externalities This session focuses on feasibility studies and the deployment of Ecomobility in freight transport. It is dedicated to both professionals and academic researchers. Smart and Green Process in Transport and LogisticsOrganized by:
FocusWith continuous developments and breakthroughs in digital and other new technologies, the logistics industry is increasingly becoming “smart.” Smart logistics enables the further optimization of logistics flows and overall freight efficiency. In the other hand, transportation, especially freight transport, has dangerous footprint on the environment, such as the impact involved by the Green House Gas (GHG) emissions, particularly CO2 emissions, which are the most worrying as they have direct repercussions on population health (e.g., pollution), and indirect ones (e.g., by the depletion of the ozone layer). Growing concerns about such unsafe impacts require revisited planning approaches by explicitly considering such bad footprints. Under the research framework focusing on smart and/or green process in logistics and its carbon footprint, this special session aims to explore and disseminate recent theoretical advances, technical applications, case studies and results relating to the modeling, optimization and resolution of vehicle routing problems, including electric ones, and particularly in a reverse logistics context, i.e. with simultaneous delivery and pick-up. Researchers and professionals are encouraged to submit papers highlighting the latest developments and practical applications of smart and green processes in transport and logistics. Viability of logistics networks, structural dynamics and recovery strategy - Low certainty context.Organized by:
Laboratoire:Research Laboratory on Development and Valorization of Resources in Desert Zones, Ibn Zohr University, Agadir, Morocco. FocusMaintaining the efficiency and profitability of logistics systems in the midst of a constantly unpredictable environment is central to the viability of logistics networks, structural dynamics and recovery strategy. This theme requires the examination of elements that affect the stability, resilience and sustainability of logistics networks, followed by actions involving adaptation strategies to cope with change, referring to risk reduction and optimization of the continuity of logistics operations. The viability of logistics networks plays a crucial role for companies operating in constantly changing contexts, given the impact of uncontrollable factors such as economic and consumer trends, unpredictable scenarios such as natural disasters and technological advances that cyclically affect the ability of logistics networks to maintain their efficiency and synergy. The structural dynamics of logistics networks are also an important consideration, with the potential for different configurations involving distribution centers, suppliers, carriers and customers to impact their efficiency and profitability. Depending on the distance between points in the supply chain, delivery times, and transportation cost, the viability of a logistics network can be influenced by its configuration. In order to address this issue, it is essential to have a solid recovery strategy. Being able to adapt to environmental changes and implement effective strategies to rehabilitate logistics networks in the event of disruption is essential. Strategies may include tasks such as improving lines of communication with supply chain partners, reducing costs, diversifying supply sources, and optimizing transportation routes. However, in an environment of low certainty, it can be difficult to predict future disruptions and plan accordingly. Companies must therefore be able to adapt quickly to changing market conditions and make quick decisions to ensure the viability of their logistics network. Optimization under Uncertainty: Methods and ApplicationsOrganized by:
FocusUncertainty is a substantial characteristic of real problems, and parameters of their mathematical formulations may be unknown beforehand. Solving optimization problems and decision making in the presence of uncertainty may be complicated compared to the deterministic situation. This session aims to address the methods of optimization under uncertainty and its applications in transportation problems, production planning and scheduling, healthcare management, and location-allocation problems. Papers that contribute to this field with convincing scientific results, real applications, methods, mathematical formulations, robust optimization approaches, stochastic optimization approaches, are of particular interest. Academic researchers and professionals are encouraged to submit their original unpublished papers following the guidelines of the conference. |
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