Loading...
Search for: constrained-optimization
0.009 seconds
Total 86 records

    Predicting the environmental economic dispatch problem for reducing waste nonrenewable materials via an innovative constraint multi-objective Chimp Optimization Algorithm

    , Article Journal of Cleaner Production ; Volume 365 , 2022 ; 09596526 (ISSN) Zhu, L ; Ren, H ; Habibi, M ; Mohammed, K. J ; Khadimallah, M. A ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    The usage of conventional fossil fuels has aided fast economic growth while also having negative consequences, such as increased global warming and the destruction of the ecosystem. This paper proposes a novel swarm-based metaheuristic method called Chimp Optimization Algorithm (ChOA) to tackle the environmental, economic dispatch issue and reducing the waste nonrenewable materials. In this regard, two objective functions named fuel cost function and emission cost function are proposed. Unique constrained handling also solves the challenge of multi-objective optimization. Standard IEEE 30 bus with six generators and a 10-unit system are used to demonstrate the usefulness of ChOA. The result... 

    A constrained multi-item EOQ inventory model for reusable items: Reinforcement learning-based differential evolution and particle swarm optimization

    , Article Expert Systems with Applications ; Volume 207 , 2022 ; 09574174 (ISSN) Fallahi, A ; Amani Bani, E ; Akhavan Niaki, S. T ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    The growing environmental concerns, governmental regulations, and significant cost savings are the primary motivations for companies to consider the reuse and recovery of products in their inventory system. The previous research ignored several realistic features of reusable items inventory systems, such as the presence of multiple products and operational constraints. For the first time, this paper presents a new multiproduct economic order quantity inventory model for an inventory system of reusable products. The goal of the model is to determine the optimal replenishment quantity and reuse quantity of each item so that the system's total cost is minimized. Several operational constraints... 

    Conical localization from angle measurements: an approximate convex solution

    , Article IEEE Sensors Letters ; Volume 6, Issue 5 , 2022 ; 24751472 (ISSN) Alamdari, E ; Behnia, F ; Amiri, R ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2022
    Abstract
    For several years, a substantial effort has been devoted to the study of 3-D source localization based on 2-D arrays by measuring the well-known azimuth and elevation angles. However, studies on 3-D source localization performed by 1-D arrays are still lacking. Perhaps, the most important drawback in the deployment of a 2-D array structure lies in the fact that it needs a planar space, which might not be available in some applications. This letter concentrates on the problem of 3-D source localization based on 1-D angle measurement provided by a linear array. Different from the traditional 2-D structures where each measurement induces a straight line, each measurement in the 1-D array... 

    Uncertain multiagent systems with distributed constrained optimization missions and event-triggered communications: application to resource allocation

    , Article IEEE Systems Journal ; 2022 , Pages 1-12 ; 19328184 (ISSN) Sarafraz, M. S ; Tavazoei, M. S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2022
    Abstract
    This article deals with solving distributed optimization problems with equality constraints by a class of uncertain nonlinear heterogeneous dynamic multiagent systems. It is assumed that each agent with an uncertain dynamic model has limited information about the main problem and limited access to the information of the state variables of the other agents. A distributed algorithm that guarantees cooperatively solving of the constrained optimization problem by the agents is proposed. Via applying this algorithm, the agents do not need to continuously broadcast their data. It is shown that the proposed algorithm can be useful in solving resource allocation problems. IEEE  

    Assessment of optimal reaction progress variable characteristics for partially premixed flames

    , Article Combustion Theory and Modelling ; Volume 26, Issue 5 , 2022 , Pages 797-830 ; 13647830 (ISSN) Chitgarha, F ; Ommi, F ; Farshchi, M ; Sharif University of Technology
    Taylor and Francis Ltd  2022
    Abstract
    The reaction progress variable is a crucial concept in the advanced flamelet combustion models. As a controlling variable, a well-defined progress variable must consider the essential features of the combustion process. It is usually a heuristically defined linear combination of some major chemical species mass fractions. However, such a simple definition could lead to inaccurate results for the fuel-rich reactive mixtures or complicated fuels, due to the vast number of chemical species in the combustion process. In this paper, a new method for generating a reaction progress variable is proposed through solving a constrained optimisation problem. The proposed method uses a genetic algorithm... 

    PVMC: Task mapping and scheduling under process variation heterogeneity in mixed-criticality systems

    , Article IEEE Transactions on Emerging Topics in Computing ; Volume 10, Issue 2 , 2022 , Pages 1166-1177 ; 21686750 (ISSN) Bahrami, F ; Ranjbar, B ; Rohbani, N ; Ejlali, A ; Sharif University of Technology
    IEEE Computer Society  2022
    Abstract
    Embedded Systems (ESs) have migrated from special-purpose hardware to commodity hardware. These systems have also tended to Mixed-Criticality (MC) implementations, executing applications of different criticalities upon a shared platform. Multi-cores, which are commonly used to design MC Systems (MCSs), bring out new challenges due to the Process Variation (PV). Power and frequency asymmetry affects the predictability of ESs. In this work, variation-aware techniques are explored to not only improve the reliability of MCSs, but also aid the scheduling and energy saving of them. We leverage the Core-to-Core (C2C) variations to protect high-criticality tasks and provide full service for a high...