Search results for: robust scheduling

Authors: Ali Abdi Kordani, Hamid Bigdelirad, Sid Mohammad Boroomandrad

Abstract:

Operating Urban Bus Transit System is a phenomenon that has a major role in transporting passengers in cities. There are many factors involved in planning and operating an Urban Bus Transit System, one of which is selecting optimized number of stops and scheduling of bus fleet departure. In this paper, we tried to introduce desirable methodology to select number of stops and schedule properly. Selecting the right number of stops causes convenience in accessibility and reduction in travel time and finally increase in public preference of this transportation mode. The achieved results revealed that number of stops must reduce from 33 to 25. Also according to scheduling and conducted economic analysis, the number of buses must decrease from 17 to 11 to have the most appropriate status for the Bus Organization.

Keywords: Number of optimized stops, organizing bus system, scheduling, urban transit.

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Authors: M. Haddadzade, M. R. Razfar, M. Farahnakian

Abstract:

Integration of process planning and scheduling functions is necessary to achieve superior overall system performance. This paper proposes a methodology for integration of process planning and scheduling for prismatic component that can be implemented in a company with existing departments. The developed model considers technological constraints whereas available time for machining in shop floor is the limiting factor to produce multiple process plan (MPP). It takes advantage of MPP while guarantied the fulfillment of the due dates via using overtime. This study has been proposed to determinate machining parameters, tools, machine and amount of over time within the minimum cost objective while overtime is considered for this. At last the illustration shows that the system performance is improved by as measured by cost and compatible with due date.

Keywords: Due date, Integration, Multiple process plan, Process planning, Scheduling.

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Authors: Phruksaphanrat B.

Abstract:

This research proposes a preemptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of makespan. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, preemptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. 

Keywords: Multi-mode resource constrained project scheduling problem, Fuzzy set, Goal programming, Preemptive fuzzy goal programming.

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Authors: Dinesh Inamadar, R. Venugopalan, K. Padmini

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An attempt has been made in the present communication to elucidate the efficacy of robust ANOVA methods to analyse horticultural field experimental data in the presence of outliers. Results obtained fortify the use of robust ANOVA methods as there was substantiate reduction in error mean square, and hence the probability of committing Type I error, as compared to the regular approach.

Keywords: Outliers, robust ANOVA, horticulture, Cook distance, Type I error.

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Authors: Lu Yanhui, Wang Chunming, Yin Changchuan, Yue Guangxin

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In this paper, we address the problem of adaptive radio resource allocation (RRA) and packet scheduling in the downlink of a cellular OFDMA system, and propose a downlink multi-carrier proportional fair (MPF) scheduler and its joint with adaptive RRA algorithm to distribute radio resources among multiple users according to their individual QoS requirements. The allocation and scheduling objective is to maximize the total throughput, while at the same time maintaining the fairness among users. The simulation results demonstrate that the methods presented provide for user more explicit fairness relative to RRA algorithm, but the joint scheme achieves the higher sum-rate capacity with flexible parameters setting compared with MPF scheduler.

Keywords: OFDMA, adaptive radio resource allocation, scheduling, QoS.

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

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This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: Time Utility Function/ Utility Accrual (TUF/UA) scheduling, Real-time system (RTS), Backward Recovery, Multiprocessor, Discrete Event Simulation (DES).

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

Abstract:

Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is then important in a first step to optimize household consumptions to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipments starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So the ceiling would no longer be fixed. The scheduling would be done on two scales, on the one hand per dwelling, and secondly, at the level of a residential complex.

Keywords: Smart grid, Energy box, Scheduling, Gang Model, Energy consumption, Energy management system, and Wireless Sensor Network.

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Authors: M. G. C. A. Cimino, G. Frosini, B. Lazzerini, F. Marcelloni

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In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is certainly one of the most known among these algorithms. In robust-FCM, noise is modeled as a separate cluster and is characterized by a prototype that has a constant distance δ from all data points. Distance δ determines the boundary of the noise cluster and therefore is a critical parameter of the algorithm. Though some approaches have been proposed to automatically determine the most suitable δ for the specific application, up to today an efficient and fully satisfactory solution does not exist. The aim of this paper is to propose a novel method to compute the optimal δ based on the analysis of the distribution of the percentage of objects assigned to the noise cluster in repeated executions of the robust-FCM with decreasing values of δ . The extremely encouraging results obtained on some data sets found in the literature are shown and discussed.

Keywords: noise prototype, robust fuzzy clustering, robustfuzzy C-means

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Authors: Hui-Jae You, Sun-Tae Chung, Souhwan Jung

Abstract:

SAD (Sum of Absolute Difference) algorithm is heavily used in motion estimation which is computationally highly demanding process in motion picture encoding. To enhance the performance of motion picture encoding on a VLIW processor, an efficient implementation of SAD algorithm on the VLIW processor is essential. SAD algorithm is programmed as a nested loop with a conditional branch. In VLIW processors, loop is usually optimized by software pipelining, but researches on optimal scheduling of software pipelining for nested loops, especially nested loops with conditional branches are rare. In this paper, we propose an optimal scheduling and implementation of SAD algorithm with conditional branch on a VLIW DSP processor. The proposed optimal scheduling first transforms the nested loop with conditional branch into a single loop with conditional branch with consideration of full utilization of ILP capability of the VLIW processor and realization of earlier escape from the loop. Next, the proposed optimal scheduling applies a modulo scheduling technique developed for single loop. Based on this optimal scheduling strategy, optimal implementation of SAD algorithm on TMS320C67x, a VLIW DSP is presented. Through experiments on TMS320C6713 DSK, it is shown that H.263 encoder with the proposed SAD implementation performs better than other H.263 encoder with other SAD implementations, and that the code size of the optimal SAD implementation is small enough to be appropriate for embedded environments.

Keywords: Optimal implementation, SAD algorithm, VLIW, TMS320C6713.

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Authors: Raksha Sharma, Vishnu Kant Soni, Manoj Kumar Mishra, Prachet Bhuyan, Utpal Chandra Dey

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Grid computing is a group of clusters connected over high-speed networks that involves coordinating and sharing computational power, data storage and network resources operating across dynamic and geographically dispersed locations. Resource management and job scheduling are critical tasks in grid computing. Resource selection becomes challenging due to heterogeneity and dynamic availability of resources. Job scheduling is a NP-complete problem and different heuristics may be used to reach an optimal or near optimal solution. This paper proposes a model for resource and job scheduling in dynamic grid environment. The main focus is to maximize the resource utilization and minimize processing time of jobs. Grid resource selection strategy is based on Max Heap Tree (MHT) that best suits for large scale application and root node of MHT is selected for job submission. Job grouping concept is used to maximize resource utilization for scheduling of jobs in grid computing. Proposed resource selection model and job grouping concept are used to enhance scalability, robustness, efficiency and load balancing ability of the grid.

Keywords: Agent, Grid Computing, Job Grouping, Max Heap Tree (MHT), Resource Scheduling.

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Authors: MohammadReza EffatParvar, Akbar Bemana, Mehdi EffatParvar

Abstract:

Scheduling algorithms are used in operating systems to optimize the usage of processors. One of the most efficient algorithms for scheduling is Multi-Layer Feedback Queue (MLFQ) algorithm which uses several queues with different quanta. The most important weakness of this method is the inability to define the optimized the number of the queues and quantum of each queue. This weakness has been improved in IMLFQ scheduling algorithm. Number of the queues and quantum of each queue affect the response time directly. In this paper, we review the IMLFQ algorithm for solving these problems and minimizing the response time. In this algorithm Recurrent Neural Network has been utilized to find both the number of queues and the optimized quantum of each queue. Also in order to prevent any probable faults in processes' response time computation, a new fault tolerant approach has been presented. In this approach we use combinational software redundancy to prevent the any probable faults. The experimental results show that using the IMLFQ algorithm results in better response time in comparison with other scheduling algorithms also by using fault tolerant mechanism we improve IMLFQ performance.

Keywords: IMLFQ, Fault Tolerant, Scheduling, Queue, Recurrent Neural Network.

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan

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Minimizing the response time to asynchronous events in a real-time system is an important factor in increasing the speed of response and an interesting concept in designing equipment fast enough for the most demanding applications. The present article will present the results regarding the validation of the nMPRA (Multi Pipeline Register Architecture) architecture using the FPGA Virtex-7 circuit. The nMPRA concept is a hardware processor with the scheduler implemented at the processor level; this is done without affecting a possible bus communication, as is the case with the other CPU solutions. The implementation of static or dynamic scheduling operations in hardware and the improvement of handling interrupts and events by the real-time executive described in the present article represent a key solution for eliminating the overhead of the operating system functions. The nMPRA processor is capable of executing a preemptive scheduling, using various algorithms without a software scheduler. Therefore, we have also presented various scheduling methods and algorithms used in scheduling the real-time tasks.

Keywords: nMPRA architecture, pipeline processor, preemptive scheduling, real-time system.

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Authors: Ponsy R.K. Sathia Bhama, Thamarai Selvi Soma Sundaram, R. Sivakama Sundari, R. Bakiyalakshmi, K. Thamizharasi

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Grid scheduling is the process of mapping grid jobs to resources over multiple administrative domains. Traditionally, application-level schedulers have been tightly integrated with the application itself and were not easily applied to other applications. This design is generic that decouples the scheduler core (the search procedure) from the application-specific (e.g. application performance models) and platform-specific (e.g. collection of resource information) components used by the search procedure. In this decoupled approach the application details are not revealed completely to broker, but customer will give the application to resource provider for execution. In a decoupled approach, apart from scheduling, the resource selection can be performed independently in order to achieve scalability.

Keywords: Meta, grid scheduling, application-level scheduler, decouple, scheduler core and performance model.

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Authors: S. Swain, P. S. Khuntia

Abstract:

In this paper an optimal convex controller is designed to control the angle of attack of a FOXTROT aircraft. Then the order of the system model is reduced to a low-dimensional state space by using Balanced Truncation Model Reduction Technique and finally the robust stability of the reduced model of the system is tested graphically by using Kharitonov rectangle and Zero Exclusion Principle for a particular range of perturbation value. The same robust stability is tested theoretically by using Frequency Sweeping Function for robust stability.

Keywords: Convex Optimization, Kharitonov Stability Criterion, Model Reduction, Robust Stability.

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Authors: P. Kanakasabapathy, Radhika. S,

Abstract:

In the competitive electricity market environment, the profit of the pumped-storage plant in the energy market can be maximized by operating it as a generator, when market clearing price is high and as a pump, to pump water from lower reservoir to upper reservoir, when the price is low. An optimal self-scheduling plan has been developed for a pumped-storage plant, carried out on weekly basis in order to maximize the profit of the plant, keeping into account of all the major uncertainties such as the sudden ancillary service delivery request and the price forecasting errors. For a pumped storage power plant to operate in a real time market successive self scheduling has to be done by considering the forecast of the day-ahead market and the modified reservoir storage due to the ancillary service request of the previous day. Sliding Window Technique has been used for successive self scheduling to ensure profit for the plant.

Keywords: Ancillary services, BPSO, Power System Economics (Electricity markets), Self-Scheduling, Sliding Window Technique.

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: Process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics.

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Authors: Chuan-Ching Sue, Shi-Zhou Chen, Ting-Yu Huang

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Dynamic bandwidth allocation in EPONs can be generally separated into inter-ONU scheduling and intra-ONU scheduling. In our previous work, the active intra-ONU scheduling (AS) utilizes multiple queue reports (QRs) in each report message to cooperate with the inter-ONU scheduling and makes the granted bandwidth fully utilized without leaving unused slot remainder (USR). This scheme successfully solves the USR problem originating from the inseparability of Ethernet frame. However, without proper setting of threshold value in AS, the number of QRs constrained by the IEEE 802.3ah standard is not enough, especially in the unbalanced traffic environment. This limitation may be solved by enlarging the threshold value. The large threshold implies the large gap between the adjacent QRs, thus resulting in the large difference between the best granted bandwidth and the real granted bandwidth. In this paper, we integrate AS with a cooperative prediction mechanism and distribute multiple QRs to reduce the penalty brought by the prediction error. Furthermore, to improve the QoS and save the usage of queue reports, the highest priority (EF) traffic which comes during the waiting time is granted automatically by OLT and is not considered in the requested bandwidth of ONU. The simulation results show that the proposed scheme has better performance metrics in terms of bandwidth utilization and average delay for different classes of packets.

Keywords: EPON, Inter-ONU and Intra-ONU scheduling, Prediction, Unused slot remainder

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Authors: Noraziah Ahmad, Roslina Mohd Sidek, Mohd Affendy Omardin

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E-Appointment Scheduling (EAS) has been developed to handle appointment for UMP students, lecturers in Faculty of Computer Systems & Software Engineering (FCSSE) and Student Medical Center. The schedules are based on the timetable and university activities. Constraints Logic Programming (CLP) has been implemented to solve the scheduling problems by giving recommendation to the users in part of determining any available slots from the lecturers and doctors- timetable. By using this system, we can avoid wasting time and cost because this application will set an appointment by auto-generated. In addition, this system can be an alternative to the lecturers and doctors to make decisions whether to approve or reject the appointments.

Keywords: EAS, Constraint Logic Programming, PHP, Apache.

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Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

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This paper studies a robust stabilization problem of a single agent in a multi-agent consensus system composed of identical agents, when the network topology of the system is completely unknown. It is shown that the transfer function of an agent in a consensus system can be described as a multiplicative perturbation of the isolated agent transfer function in frequency domain. From an existing robust stabilization result, we present sufficient conditions for a robust stabilization of an agent against unknown network topology.

Keywords: Multi-agent System, Robust Stabilization, Transfer Function.

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Authors: Smajo Bisanovic, Mensur Hajro, Muris Dlakic

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This paper presents one comprehensive modelling approach for maintenance scheduling problem of thermal power units in competitive market. This problem is formulated as a 0/1 mixedinteger linear programming model. Model incorporates long-term bilateral contracts with defined profiles of power and price, and weekly forecasted market prices for market auction. The effectiveness of the proposed model is demonstrated through case study with detailed discussion.

Keywords: Maintenance scheduling, bilateral contracts, market prices, profit.

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Authors: Zixin Liu

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The problem of robust stability and robust stabilization for a class of discrete-time uncertain systems with time delay is investigated. Based on Tchebychev inequality, by constructing a new augmented Lyapunov function, some improved sufficient conditions ensuring exponential stability and stabilization are established. These conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. Compared with some previous results derived in the literature, the new obtained criteria have less conservatism. Two numerical examples are provided to demonstrate the improvement and effectiveness of the proposed method.

Keywords: Robust stabilization, robust stability, discrete-time system, time delay.

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Authors: Jae-Min Yu, Hyoung-Ho Doh, Ji-Su Kim, Dong-Ho Lee, Sung-Ho Nam

Abstract:

A reconfigurable manufacturing system (RMS) is an advanced system designed at the outset for rapid changes in its hardware and software components in order to quickly adjust its production capacity and functionally. Among various operational decisions, this study considers the scheduling problem that determines the input sequence and schedule at the same time for a given set of parts. In particular, we consider the practical constraints that the numbers of pallets/fixtures are limited and hence a part can be released into the system only when the fixture required for the part is available. To solve the integrated input sequencing and scheduling problems, we suggest a priority rule based approach in which the two sub-problems are solved using a combination of priority rules. To show the effectiveness of various rule combinations, a simulation experiment was done on the data for a real RMS, and the test results are reported.

Keywords: Reconfigurable manufacturing system, scheduling, priority rules, multiple process plans, pallets/fixtures

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Authors: Kuo-Lung Wu

Abstract:

The weighting exponent m is called the fuzzifier that can have influence on the clustering performance of fuzzy c-means (FCM) and mÎ[1.5,2.5] is suggested by Pal and Bezdek [13]. In this paper, we will discuss the robust properties of FCM and show that the parameter m will have influence on the robustness of FCM. According to our analysis, we find that a large m value will make FCM more robust to noise and outliers. However, if m is larger than the theoretical upper bound proposed by Yu et al. [14], the sample mean will become the unique optimizer. Here, we suggest to implement the FCM algorithm with mÎ[1.5,4] under the restriction when m is smaller than the theoretical upper bound.

Keywords: Fuzzy c-means, robust, fuzzifier.

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Authors: Parviz Fattahi

Abstract:

Scheduling for the flexible job shop is very important in both fields of production management and combinatorial optimization. However, it quit difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. In this paper, a Pareto approach to solve the multi objective flexible job shop scheduling problems is proposed. The objectives considered are to minimize the overall completion time (makespan) and total weighted tardiness (TWT). An effective simulated annealing algorithm based on the proposed approach is presented to solve multi objective flexible job shop scheduling problem. An external memory of non-dominated solutions is considered to save and update the non-dominated solutions during the solution process. Numerical examples are used to evaluate and study the performance of the proposed algorithm. The proposed algorithm can be applied easily in real factory conditions and for large size problems. It should thus be useful to both practitioners and researchers.

Keywords: Flexible job shop, Scheduling, Hierarchical approach, simulated annealing, tabu search, multi objective.

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Authors: Seyed Habib A. Rahmati

Abstract:

During last decades, developing multi-objective evolutionary algorithms for optimization problems has found considerable attention. Flexible job shop scheduling problem, as an important scheduling optimization problem, has found this attention too. However, most of the multi-objective algorithms that are developed for this problem use nonprofessional approaches. In another words, most of them combine their objectives and then solve multi-objective problem through single objective approaches. Of course, except some scarce researches that uses Pareto-based algorithms. Therefore, in this paper, a new Pareto-based algorithm called controlled elitism non-dominated sorting genetic algorithm (CENSGA) is proposed for the multi-objective FJSP (MOFJSP). Our considered objectives are makespan, critical machine work load, and total work load of machines. The proposed algorithm is also compared with one the best Pareto-based algorithms of the literature on some multi-objective criteria, statistically.

Keywords: Scheduling, Flexible job shop scheduling problem, controlled elitism non-dominated sorting genetic algorithm

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Authors: Mahdi Hamzeh, Sied Mehdi Fakhraie, Caro Lucas

Abstract:

All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.

Keywords: Computational complexity, Deadline, Feasible scheduling, Fuzzy scheduling, Priority, Real-time multiprocessor systems, Robustness, System utilization.

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Authors: Hossein Nourkhiz Mahjoub, Mohsen Shiva

Abstract:

Wireless Mesh Networking is a promising proposal for broadband data transmission in a large area with low cost and acceptable QoS. These features- trade offs in WMNs is a hot research field nowadays. In this paper a mathematical optimization framework has been developed to maximize throughput according to upper bound delay constraints. IEEE 802.11 based infrastructure backhauling mode of WMNs has been considered to formulate the MINLP optimization problem. Proposed method gives the full routing and scheduling procedure in WMN in order to obtain mentioned goals.

Keywords: Mixed-Integer Non Linear Programming (MINLP), routing and scheduling, throughput, wireless mesh networks (WMNs)

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Authors: Saleem Z. Ramadan, Gürsel A. Süer

Abstract:

In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.

Keywords: Machine scheduling, Genetic algorithms, Due dates, Number of tardy jobs, Number of early jobs, Integer programming, Dual Fitness functions.

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Authors: Halil Ibrahim Demir, Abdullah Hulusi Kokcam, Fuat Simsir, Özer Uygun

Abstract:

Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure.

Keywords: Evolutionary strategies, hybrid searches, process planning, simulated annealing, weighted due-date assignment, weighted scheduling.

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Authors: Mansoor Momeni, Mahmoud Dehghan Nayeri, Ali Faal Ghayoumi, Hoda Ghorbani

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This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.

Keywords: Financial data analysis, Influential data, Outliers, Robust regression.

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