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Lotfi Hidri
Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia

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Journal article
Published: 18 August 2021 in Sustainability
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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%.

ACS Style

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 Style

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 (16):9277.

Chicago/Turabian Style

Lotfi 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.

Journal article
Published: 08 April 2021 in Processes
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This research focuses on the problem of scheduling a set of jobs on unrelated parallel machines subject to release dates, sequence-dependent setup times, and additional renewable resource constraints. The objective is to minimize the maximum completion time (makespan). To optimize the problem, a modified harmony search (MHS) algorithm was proposed. The parameters of MHS are regulated using full factorial analysis. The MHS algorithm is examined, evaluated, and compared to the best methods known in the literature. Four algorithms were represented from similar works in the literature. A benchmark instance has been established to test the sensitivity and behavior of the problem parameters of the different algorithms. The computational results of the MHS algorithm were compared with those of other metaheuristics. The competitive performance of the developed algorithm is verified, and it was shown to provide a 42% better solution than the others.

ACS Style

Ibrahim Al-Harkan; Ammar Qamhan; Ahmed Badwelan; Ali Alsamhan; Lotfi Hidri. Modified Harmony Search Algorithm for Resource-Constrained Parallel Machine Scheduling Problem with Release Dates and Sequence-Dependent Setup Times. Processes 2021, 9, 654 .

AMA Style

Ibrahim Al-Harkan, Ammar Qamhan, Ahmed Badwelan, Ali Alsamhan, Lotfi Hidri. Modified Harmony Search Algorithm for Resource-Constrained Parallel Machine Scheduling Problem with Release Dates and Sequence-Dependent Setup Times. Processes. 2021; 9 (4):654.

Chicago/Turabian Style

Ibrahim Al-Harkan; Ammar Qamhan; Ahmed Badwelan; Ali Alsamhan; Lotfi Hidri. 2021. "Modified Harmony Search Algorithm for Resource-Constrained Parallel Machine Scheduling Problem with Release Dates and Sequence-Dependent Setup Times." Processes 9, no. 4: 654.

Journal article
Published: 05 February 2021 in Metals
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Presently, friction stir spot welding (FSSW) has become a common alternative for spot welding technologies. Over the years, researchers have implemented various methods for enhancing weld strength. However, the literature shows that the previously reported approaches have used static (constant) welding parameters set at the beginning of the welding stroke (i.e., the FSSW parameters were kept constant during the welding stroke). In contrast, in this study, an innovative technique is proposed for enhancing the weld strength for Al 1050 material by adjusting the FSSW process parameters during the welding stroke. Two FSSW parameters, namely, feed rate and spindle speed (dynamic parameters), are used in this study with a stepwise variation function and are changed during the welding stroke. The results of this study show that the weld tensile strength is enhanced by 12–21% when using the proposed novel dynamic welding parameter technique. This is a significant increase in the weld strength compared to when static welding parameters are employed during the welding stroke.

ACS Style

Ahmed Badwelan; Ali Al-Samhan; Saqib Anwar; Lotfi Hidri. Novel Technique for Enhancing the Strength of Friction Stir Spot Welds through Dynamic Welding Parameters. Metals 2021, 11, 280 .

AMA Style

Ahmed Badwelan, Ali Al-Samhan, Saqib Anwar, Lotfi Hidri. Novel Technique for Enhancing the Strength of Friction Stir Spot Welds through Dynamic Welding Parameters. Metals. 2021; 11 (2):280.

Chicago/Turabian Style

Ahmed Badwelan; Ali Al-Samhan; Saqib Anwar; Lotfi Hidri. 2021. "Novel Technique for Enhancing the Strength of Friction Stir Spot Welds through Dynamic Welding Parameters." Metals 11, no. 2: 280.

Journal article
Published: 06 November 2020 in Mathematics
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Hospitals are facing an important financial pressure due to the increasing of the operating costs. Indeed, the growth for the hospitals’ services demand causes a rising in the number of required qualified personnel. Enlarging the personnel number increases dramatically the fixed total cost. Based on some studies, 50% of operating costs in US hospitals are allocated to healthcare personnel. Therefore, reducing these types of costs without damaging the service quality becomes a priority and an obligation. In this context, several studies focused on minimizing the total cost by producing optimal or near optimal schedules for nurses and physicians. In this paper, a real-life physicians scheduling problem with cost minimization is addressed. This problem is encountered in an Intensive Care Unit (ICU) where the current schedule is manually produced. The manual schedule is generating a highly unbalanced load within physicians in addition to a high cost overtime. The manual schedule preparation is a time consuming procedure. The main objective of this work is to propose a procedure that systematically produces an optimal schedule. This optimal schedule minimizes the total overtime within a short time and should satisfies the faced constraints. The studied problem is mathematically formulated as an integer linear program. The constraints are real, hard, and some of them are non-classical ones (compared to the existing literature). The obtained mathematical model is solved using a state-of-the-art software. Experimental tests on real data have shown the performance of the proposed procedure. Indeed, the new optimal schedules reduce the total overtime by up to 69%. In addition, a more balanced workload for physicians is obtained and several physician preferences are now satisfied.

ACS Style

Lotfi Hidri; Achraf Gazdar; Mohammed M. Mabkhot. Optimized Procedure to Schedule Physicians in an Intensive Care Unit: A Case Study. Mathematics 2020, 8, 1976 .

AMA Style

Lotfi Hidri, Achraf Gazdar, Mohammed M. Mabkhot. Optimized Procedure to Schedule Physicians in an Intensive Care Unit: A Case Study. Mathematics. 2020; 8 (11):1976.

Chicago/Turabian Style

Lotfi Hidri; Achraf Gazdar; Mohammed M. Mabkhot. 2020. "Optimized Procedure to Schedule Physicians in an Intensive Care Unit: A Case Study." Mathematics 8, no. 11: 1976.

Research article
Published: 09 April 2020 in Advances in Materials Science and Engineering
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The selection of manufacturing processes for a given application is a complex problem of multicriteria decision-making although there have been several different approaches that can be utilized to select a suitable alternative. However, identifying appropriate multicriteria decision-making approach from the list of available methods for a given application is a difficult task. This work suggests a methodology to assess different selection approaches, which are the technique for order of preference by similarity to ideal solution (TOPSIS), analytic hierarchy process (AHP), and VIKOR: stepwise procedure. This valuation was done depending on the following factors: number of alternative processes and criteria, agility through the process of decision-making, computational complexity, adequacy in supporting a group decision, and addition or removal of a criterion. A case study in this study was presented to analyse the evaluation methodology. The criteria used to evaluate and identify the best manufacturing process were categorized into productivity, accuracy, complexity, flexibility, material utilization, quality, and operation cost. Five manufacturing processes were considered, including gravity die casting, investment casting, pressure die casting, sand casting, and additive manufacturing. The results showed that each approach was suitable for the problems of manufacturing process selection, in particular toward the support of group decision-making and uncertainty modelling. Manufacturing processes were ranked based on their respective weights for AHP, TOPSIS, and VIKOR, and sand casting is the best. In terms of computational complexity, the VIKOR method performed better than TOPSIS and AHP. Moreover, the VIKOR and TOPSIS methods were better convenient to the selection of manufacturing processes for agility during the process of decision-making, the number of alternative processes and criteria, adequacy in supporting a group decision, and addition or removal of a criterion.

ACS Style

Atef M. Ghaleb; Husam Kaid; Ali Alsamhan; Syed Hammad Mian; Lotfi Hidri. Assessment and Comparison of Various MCDM Approaches in the Selection of Manufacturing Process. Advances in Materials Science and Engineering 2020, 2020, 1 -16.

AMA Style

Atef M. Ghaleb, Husam Kaid, Ali Alsamhan, Syed Hammad Mian, Lotfi Hidri. Assessment and Comparison of Various MCDM Approaches in the Selection of Manufacturing Process. Advances in Materials Science and Engineering. 2020; 2020 ():1-16.

Chicago/Turabian Style

Atef M. Ghaleb; Husam Kaid; Ali Alsamhan; Syed Hammad Mian; Lotfi Hidri. 2020. "Assessment and Comparison of Various MCDM Approaches in the Selection of Manufacturing Process." Advances in Materials Science and Engineering 2020, no. : 1-16.

Journal article
Published: 25 September 2019 in Knowledge-Based Systems
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The objective of a recommender system is to provide customers with personalized recommendations while selecting an item among a set of products (movies, books, etc.). The collaborative filtering is the most used technique for recommender systems. One of the main components of a recommender system based on the collaborative filtering technique, is the similarity measure used to determine the set of users having the same behavior with regard to the selected items. Several similarity functions have been proposed, with different performances in terms of accuracy and quality of recommendations. In this paper, we propose a new simple and efficient similarity measure. Its mathematical expression is determined through the following paper contributions: 1) transforming some intuitive and qualitative conditions, that should be satisfied by the similarity measure, into relevant mathematical equations namely: the integral equation, the linear system of differential equations and a non-linear system and 2) resolving the equations to achieve the kernel function of the similarity measure. The extensive experimental study driven on a benchmark datasets shows that the proposed similarity measure is very competitive, especially in terms of accuracy, with regards to some representative similarity measures of the literature.

ACS Style

Achraf Gazdar; Lotfi Hidri. A new similarity measure for collaborative filtering based recommender systems. Knowledge-Based Systems 2019, 188, 105058 .

AMA Style

Achraf Gazdar, Lotfi Hidri. A new similarity measure for collaborative filtering based recommender systems. Knowledge-Based Systems. 2019; 188 ():105058.

Chicago/Turabian Style

Achraf Gazdar; Lotfi Hidri. 2019. "A new similarity measure for collaborative filtering based recommender systems." Knowledge-Based Systems 188, no. : 105058.

Research article
Published: 21 August 2019 in Advances in Materials Science and Engineering
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In nowadays industry 4.0 and changeable manufacturing context, designers and manufacturing engineers struggle to determine appropriate quick, accurate (with flawless quality), and cost-effective processes to design highly customized products to meet customer requirements. To determine manufacturing processes, the matching between product features, material characteristics, and process capabilities needs to be optimized. Finding such an optimized matching is usually referred to as manufacturing process selection (MPS), which is not an easy task because of the infinite combinations of product features, numerous material characteristics, and various manufacturing processes. Although problems associated with MPS have received considerable attention, semantic web technologies are still underexplored and their potential is still uncovered. Almost no previous study has considered combining case-based reasoning (CBR) with ontologies, a famous and powerful semantic web enabler, to achieve MPS. In this study, we developed a decision support system (DSS) for MPS based on ontology-enabled CBR. By applying automatic reasoning and similarity retrieving on an industrial case study, we show that ontologies enable process selection by determining competitive matching between product features, material characteristics, and process capabilities and by endorsing effective case retrieval.

ACS Style

Mohammed M. Mabkhot; Ali Alsamhan; Lotfi Hidri. An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection. Advances in Materials Science and Engineering 2019, 2019, 1 -18.

AMA Style

Mohammed M. Mabkhot, Ali Alsamhan, Lotfi Hidri. An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection. Advances in Materials Science and Engineering. 2019; 2019 ():1-18.

Chicago/Turabian Style

Mohammed M. Mabkhot; Ali Alsamhan; Lotfi Hidri. 2019. "An Ontology-Enabled Case-Based Reasoning Decision Support System for Manufacturing Process Selection." Advances in Materials Science and Engineering 2019, no. : 1-18.

Conference paper
Published: 01 May 2016 in IOP Conference Series: Materials Science and Engineering
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In this paper, we consider a case study for the problem of physicians scheduling in an Intensive Care Unit (ICU). The objective is to minimize the total overtime under complex constraints. The considered ICU is composed of three buildings and the physicians are divided accordingly into six teams. The workload is assigned to each team under a set of constraints. The studied problem is composed of two simultaneous phases: composing teams and assigning the workload to each one of them. This constitutes an additional major hardness compared to the two phase's process: composing teams and after that assigning the workload. The physicians schedule in this ICU is used to be done manually each month. In this work, the studied physician scheduling problem is formulated as an integer linear program and solved optimally using state of the art software. The preliminary experimental results show that 50% of the overtime can be saved.

ACS Style

L Hidri; M Labidi. Optimal physicians schedule in an Intensive Care Unit. IOP Conference Series: Materials Science and Engineering 2016, 131, 012001 .

AMA Style

L Hidri, M Labidi. Optimal physicians schedule in an Intensive Care Unit. IOP Conference Series: Materials Science and Engineering. 2016; 131 ():012001.

Chicago/Turabian Style

L Hidri; M Labidi. 2016. "Optimal physicians schedule in an Intensive Care Unit." IOP Conference Series: Materials Science and Engineering 131, no. : 012001.

Research article
Published: 21 December 2014 in The Scientific World Journal
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We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures.

ACS Style

Lotfi Hidri; Anis Gharbi; Mohamed Aly Louly. Efficient Bounding Schemes for the Two-Center Hybrid Flow Shop Scheduling Problem with Removal Times. The Scientific World Journal 2014, 2014, 1 -7.

AMA Style

Lotfi Hidri, Anis Gharbi, Mohamed Aly Louly. Efficient Bounding Schemes for the Two-Center Hybrid Flow Shop Scheduling Problem with Removal Times. The Scientific World Journal. 2014; 2014 ():1-7.

Chicago/Turabian Style

Lotfi Hidri; Anis Gharbi; Mohamed Aly Louly. 2014. "Efficient Bounding Schemes for the Two-Center Hybrid Flow Shop Scheduling Problem with Removal Times." The Scientific World Journal 2014, no. : 1-7.