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Global warming and climate change are threatening life on earth. These changes are due to human activities resulting in the emission of greenhouse gases. This is caused by intensive industrial activities and excessive fuel energy consumption. Recently, the scheduling of production systems has been judged to be an effective way to reduce energy consumption. This is the field of green scheduling, which aims to allocate jobs to machines in order to minimize total costs, with a focus on the sustainable use of energy. Several studies have investigated parallel-machine shops, with a special focus on reducing and minimizing the total consumed energy. Few studies explicitly include the idle energy of parallel machines, which is the energy consumed when the machines are idle. In addition, very few studies have considered the elimination of idle machine times as an efficient way to reduce the total consumed energy. This is the no-idle machine constraint, which is the green aspect of the research. In this context, this paper addresses the green parallel-machine scheduling problem, including release dates, delivery times, and no-idle machines, with the objective of minimizing the maximum completion time. This problem is of practical interest since it is encountered in several industry processes, such as the steel and automobile industries. A mixed-integer linear programming (MILP) model is proposed for use in obtaining exact solutions for small-sized instances. Due to the NP-hardness of the studied problem, and encouraged by the successful adaptation of metaheuristics for green scheduling problems, three genetic algorithms (GAs) using three different crossover operators and a simulated annealing algorithm (SA) were developed for large-sized problems. A new family of lower bounds is proposed. This was intended for the evaluation of the performance of the proposed algorithms over the average percent of relative deviation (ARPD). In addition, the green aspect was evaluated over the percentage of saved energy, while eliminating the idle-machine times. An extensive experimental study was carried out on a benchmark of test problems with up to 200 jobs and eight machines. This experimental study showed that one GA variant dominated the other proposed procedures. Furthermore, the obtained numerical results provide strong evidence that the proposed GA variant outperformed the existing procedures from the literature. The experimental study also showed that the adoption of the no-idle machine time constraints made it possible to reduce the total consumed energy by 29.57%, while the makespan (cost) increased by only 0.12%.
Lotfi Hidri; Ali Alqahtani; Achraf Gazdar; Belgacem Ben Youssef. Green Scheduling of Identical Parallel Machines with Release Date, Delivery Time and No-Idle Machine Constraints. Sustainability 2021, 13, 9277 .
AMA StyleLotfi Hidri, Ali Alqahtani, Achraf Gazdar, Belgacem Ben Youssef. Green Scheduling of Identical Parallel Machines with Release Date, Delivery Time and No-Idle Machine Constraints. Sustainability. 2021; 13 (16):9277.
Chicago/Turabian StyleLotfi Hidri; Ali Alqahtani; Achraf Gazdar; Belgacem Ben Youssef. 2021. "Green Scheduling of Identical Parallel Machines with Release Date, Delivery Time and No-Idle Machine Constraints." Sustainability 13, no. 16: 9277.
We report simulation results describing cell-cell interactions using a versatile computational model to simulate the growth of multicellular tissues employing a discrete approach based on cellular automata. In particular, we present results of cell collision and aggregation for three cell populations each having its own division and motion characteristics based on experimental data. The developed model allows us to study the tissue growth rates and population dynamics of different populations of migrating and proliferating mammalian cells in a mixed and segmented seeding distribution. In this regard, the model assumes that nutrient and growth factor concentrations remain constant in space and time. Cell migration is modeled using a discrete-time Markov chain approach. Both heterotypic and homotypic cell-cell interactions play important roles in cell and tissue functions. The temporal evolution of the frequency of cell collision and aggregation and their relations to other variables that quantify some of the dynamics of cell populations can be predicted by this model for different cell seeding distributions.
Belgacem Ben Youssef. Simulating Cell-Cell Interactions Using a Multicellular Three-Dimensional Computational Model of Tissue Growth. Privacy Enhancing Technologies 2018, 215 -228.
AMA StyleBelgacem Ben Youssef. Simulating Cell-Cell Interactions Using a Multicellular Three-Dimensional Computational Model of Tissue Growth. Privacy Enhancing Technologies. 2018; ():215-228.
Chicago/Turabian StyleBelgacem Ben Youssef. 2018. "Simulating Cell-Cell Interactions Using a Multicellular Three-Dimensional Computational Model of Tissue Growth." Privacy Enhancing Technologies , no. : 215-228.
We explore some aspects of cell population dynamics in a wound-healing environment using a three-dimensional simulation model for multicellular tissue growth. The computational model uses a discrete approach based on cellular automata to simulate wound-healing times and tissue growth rates of multiple populations of proliferating and migrating cells. Each population of cells has its own division, motion, collision, and aggregation characteristics resulting in a number of useful system parameters that allow us to investigate their emergent effects. These random dynamic processes can be modeled by appropriately choosing the governing rules of the state transitions of each computational site. Discrete systems of this kind constitute an important approach for studying the temporal dynamics of complex biological systems.
Belgacem Ben Youssef. Exploring the Effect of Cell Heterogeneity in Wound Healing Using a 3D Multicellular Tissue Growth Model. Computer Algebra in Scientific Computing 2015, 109 -120.
AMA StyleBelgacem Ben Youssef. Exploring the Effect of Cell Heterogeneity in Wound Healing Using a 3D Multicellular Tissue Growth Model. Computer Algebra in Scientific Computing. 2015; ():109-120.
Chicago/Turabian StyleBelgacem Ben Youssef. 2015. "Exploring the Effect of Cell Heterogeneity in Wound Healing Using a 3D Multicellular Tissue Growth Model." Computer Algebra in Scientific Computing , no. : 109-120.
We present the simulation of the effect of cell migration speed on wound healing using a three-dimensional computational model for multicellular tissue growth. The computational model uses a discrete approach based on cellular automata to simulate wound-healing times and tissue growth rates of multiple populations of proliferating and migrating cells. Each population of cells has its own division, motion, collision, and aggregation characteristics resulting in a number of useful system parameters that allow us to investigate their emergent effects. Our sequential performance results point to the need of porting the model to modern high performance machines to harness the computational power available in multicore and GPU-based computers. Discrete systems of this kind can be a valuable approach for studying many complex systems, including biological ones.
Belgacem Ben Youssef. Simulating the Effect of Cell Migration Speed on Wound Healing Using a 3D Cellular Automata Model for Multicellular Tissue Growth. Computer Algebra in Scientific Computing 2015, 28 -42.
AMA StyleBelgacem Ben Youssef. Simulating the Effect of Cell Migration Speed on Wound Healing Using a 3D Cellular Automata Model for Multicellular Tissue Growth. Computer Algebra in Scientific Computing. 2015; ():28-42.
Chicago/Turabian StyleBelgacem Ben Youssef. 2015. "Simulating the Effect of Cell Migration Speed on Wound Healing Using a 3D Cellular Automata Model for Multicellular Tissue Growth." Computer Algebra in Scientific Computing , no. : 28-42.
Besides generating faster solutions, parallel computers can be used to solve bigger or more complex problems. In particular, they can be utilized to run simulations at finer resolutions and to model physical phenomena more realistically. We describe in this article the development of a parallel cellular automata algorithm used in the three-dimensional simulation of multicellular tissue growth. Computational models of this genre are becoming ever more important because they provide an alternative approach to continuous models and an ability to describe the dynamics of complex biological systems evolving in time. We report on the different components of the model where cellular automata is used to model different types of cell populations that execute persistent random walks on the computational grid, collide, aggregate, and proliferate until they reach confluence. We elaborate on the main issues encountered in the parallelization of the algorithm as well as its implementation on a parallel machine with a particular focus on maintaining determinism. By delaying the exchange of cells in the shared boundaries between neighboring processors till after all events related to cell division and motion are accounted for in a given time step, good parallel performance results are obtained on a high-performance cluster.
Belgacem Ben Youssef. A parallel cellular automata algorithm for the deterministic simulation of 3-D multicellular tissue growth. Cluster Computing 2015, 18, 1561 -1579.
AMA StyleBelgacem Ben Youssef. A parallel cellular automata algorithm for the deterministic simulation of 3-D multicellular tissue growth. Cluster Computing. 2015; 18 (4):1561-1579.
Chicago/Turabian StyleBelgacem Ben Youssef. 2015. "A parallel cellular automata algorithm for the deterministic simulation of 3-D multicellular tissue growth." Cluster Computing 18, no. 4: 1561-1579.
Data Visualization affords us the ability to explore the spatial and temporal domains of many time-varying phenomena. In this article, we describe our application of visualization to a three-dimensional simulation model for tissue growth. We review the different components of the model where cellular automata is used to model populations of cells that execute persistent random walks, collide, and proliferate until they reach confluence. We then describe the system architecture of the developed visualization tool, the employed rendering techniques, and the related prototyping interfaces. We also discuss some of the visualization results obtained thus far that are pertinent to enhancing the validity of the computational model. This visualization tool could be useful in facilitating the research of scientists by providing them with meaningful means to interpret and analyze simulation data and to compare them to experimental results. Our objective in this work is to develop computer-aided design solutions that support the simulation of tissue growth and its design exploration.
Belgacem Ben Youssef. A visualization tool of 3-D time-varying data for the simulation of tissue growth. Multimedia Tools and Applications 2013, 73, 1795 -1817.
AMA StyleBelgacem Ben Youssef. A visualization tool of 3-D time-varying data for the simulation of tissue growth. Multimedia Tools and Applications. 2013; 73 (3):1795-1817.
Chicago/Turabian StyleBelgacem Ben Youssef. 2013. "A visualization tool of 3-D time-varying data for the simulation of tissue growth." Multimedia Tools and Applications 73, no. 3: 1795-1817.