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Mathematical Modeling and Metaheuristic Optimization for Distributed No-Wait Flow Shop Scheduling in Desalination Systems
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Author(s): Achraf Sayah (Higher Normal School, Hassan II University, Morocco), Said Aqil (National Higher School of Arts And Crafts, Hassan II University, Morocco)and Mohamed Lahby (Higher Normal School, Hassan II University, Morocco)
Copyright: 2026
Pages: 28
Source title:
Computational Intelligence and Optimization Methods for Sustainable Water Management
Source Author(s)/Editor(s): Yassine Ezaier (Hassan II University, Casablanca, Morocco), Rajae Gaamouche (Moroccan School of Engineering Sciences, Rabat, Morocco)and Mohamed Lahby (Hassan II University, Casablanca, Morocco)
DOI: 10.4018/979-8-3373-2700-6.ch008
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Abstract
Desalination is an innovative solution to the global water shortage; however, scheduling and resource allocation in these systems present significant challenges. To address these challenges, this paper investigates the application of metaheuristic optimization techniques to enhance the performance of distributed desalination systems. The problem is formulated as a distributed flow shop scheduling model, with the primary objective of minimizing total flow time (TFT) to ensure timely water production and operational efficiency. To solve this, three metaheuristics are proposed: Iterated Greedy, Iterative Local Search, and Variable Neighborhood Search. The effectiveness of these metaheuristics is enhanced using two initialization techniques: NEH and GRASP, yielding a total of six approaches. A comprehensive simulation study was conducted on a set of benchmark instances. The results show that all proposed metaheuristics provide valuable solutions for minimizing TFT and optimizing resource allocation, with varying levels of performance across different instances.
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