Dynamic Multi-objective Optimization (DMO) is a challenging research topic since the objective functions, constraints, and problem parameters may change over time. Several evolutionary algorithms have been proposed to deal with DMO problems. Nevertheless, they were restricted unconstrained or domain constrained In this work, we focus on dynamicty of constraints along time-varying functions. As very recent area, observed lack benchmarks that simultaneously take into account these...

Dynamic multi-objective optimization problems involve the simultaneous of several competing objectives where objective functions and/or constraints may change over time. Evolutionary algorithms have been considered as popular approaches to solve such problems. Despite considerable number studies reported in evolutionary dynamic environments, most them are restricted single case. Moreover, majority based on use some techniques detect or predict changes which is sometimes difficult even...

Model-Based System Engineering (MBSE) is an increasingly important methodology to support system engineering and has attained a high level of attentiveness in business simulation practices as conceptual modelling approach. In this paper, we present our results related the application MBSE approaches complex semiconductor manufacturing supply chain planning systems. We investigate Modeling Language (SysML), Web Ontology (OWL) Business Process Notation (BPMN) different languages for MBSE....

Where demand outstrips supply, there will result in shortages to end customers. In such a case decisions need be made of how allocate supply Customer satisfaction requires accurate order promising that leads better cooperation, as well trustable orders and forecasts from As result, customer through system more planning for production. this regard, modern Advanced Planning Systems (APS) provides allocation customers’ based on “Available To Promise” (ATP). Lack escalation, excess are propelled...

In parallel to optimizing energy consumption within houses, users' comfort is increasingly considered as an essential success criterion for automated smart home solutions. From the user perspective, balancing trade-offs between and when scheduling appliances a challenging task mainly dynamic context (energy price, budget, preferences, source, etc). To address this challenge, paper has modeled constrained multi-objective optimization problem have leveraged recently introduced evolutionary...

Several real world problems have two levels of optimization instead a single one. These are said to be bi-level and so computationally expensive solve since the evaluation each upper level solution requires finding an optimal at lower level. Most existing works in this direction focused on continuous problems. Motivated by observation, we propose paper improved version our recently proposed algorithm CODBA (CO-evolutionary Decomposition-Based Algorithm), called CODBA-II, tackle combinatorial...

In the growing globalization of production systems, complexity supply chains as socio-technical systems is escalating which, consequently, increases importance strong planning systems. Plans are developed to structure in end-to-end that can experience nervousness due uncertainties results unsatisfied customers. Although external causes and instabilities chain were previously considered literature, internal these complex networks result from how sub-components system interact. To study...

During the two last decades, evolutionary algorithms have been successfully used to solve multiobjective optimization problems. Several works established improve convergence and diversity. Recently, several artificial immune systems shown their ability However, in reality, decision makers are not interested with whole optimal Pareto front rather than portion of that matches at most preferences, i.e., region interest. In this paper, we propose a new dominance relation inspired from ideas...

A semiconductor manufacturing Supply Chain (SC) starts with intricate processes within fabrications and test facilities that typically span a global network. To manage these complex SCs, an Advanced Planning System (APS) is required. APS has open architecture allows custom integration of modules algorithms are required to create stable SC plans. However, nervousness instabilities in planning system inevitable. In this paper, we demonstrate simulation framework simulate the interaction...

Digital Twins (DTs) have emerged as a powerful technology that enables manufacturing companies to build virtual representations of physical systems or assets, allowing them monitor, analyze, and optimize their Operations for Supply Chain Management (OSCM) systems. By leveraging the capabilities data analytics, IoT sensors, cloud computing, digital twins can help organizations gain insight into operations supply chain networks, improve production efficiency, reduce downtime, enhance overall...