Search results for: resource planing and scheduling

Authors: Norhayati Mohd Rasip, Abd. Samad Hasan Basari , Nuzulha Khilwani Ibrahim, Burairah Hussin

Abstract:

The allocation of working schedule especially for shift environment is hard to fulfill its fairness among them. In the case of nurse scheduling, to set up the working time table for them is time consuming and complicated, which consider many factors including rules, regulation and human factor. The scenario is more complicated since most nurses are women which have personnel constraints and maternity leave factors. The undesirable schedule can affect the nurse productivity, social life and the absenteeism can significantly as well affect patient's life. This paper aimed to enhance the scheduling process by utilizing the particle swarm optimization in order to solve nurse scheduling problem. The result shows that the generated multiple initial schedule is fulfilled the requirements and produces the lowest cost of constraint violation.

Keywords: nurse scheduling, particle swarm optimisation, nurse rostering, hard and soft constraint

Procedia PDF Downloads 337

Authors: Chun-Chuan Yang, Jeng-Yueng Chen, Yi-Ting Mai, Chen-Ming Yang

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In this paper, the design of integrated sleep scheduling for relay nodes and user equipments under a Donor eNB (DeNB) in the mode of Time Division Duplex (TDD) in LTE-A is presented. The idea of virtual time is proposed to deal with the discontinuous pattern of the available radio resource in TDD, and based on the estimation of the traffic load, three power saving schemes in the top-down strategy are presented. Associated mechanisms in each scheme including calculation of the virtual subframe capacity, the algorithm of integrated sleep scheduling, and the mapping mechanisms for the backhaul link and the access link are presented in the paper. Simulation study shows the advantage of the proposed schemes in energy saving over the standard DRX scheme.

Keywords: LTE-A, relay, TDD, power saving

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Authors: Sapan Tiwari, Namrata Ghosh

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In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

Procedia PDF Downloads 127

Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

Procedia PDF Downloads 238

Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

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This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: flexible job shop scheduling, decision tree, priority rules, case study

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

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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: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

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Minimizing the number of tardy jobs is an important factor to consider while making scheduling decisions. This is because on-time shipments are vital for lowering cost and increasing customers’ satisfaction. This paper addresses the single machine scheduling problem with the objective of minimizing the number of tardy jobs. The only known information is the lower and upper bounds for processing times, and deterministic job due dates. A dominance relation is established, and an algorithm is proposed. Several heuristics are generated from the proposed algorithm. Computational analysis indicates that the performance of one of the heuristics is very close to the optimal solution, i.e., on average, less than 1.5 % from the optimal solution.

Keywords: single machine scheduling, number of tardy jobs, heuristi, lower and upper bounds

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Authors: Farzad Pargar

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We introduce the preventive maintenance and renewal scheduling problem for a multi-unit system over a finite and discretized time horizon. Given the latest possible time for carrying out the next maintenance and renewal projects after the previous ones and considering several common set-up costs, the introduced scheduling model tries to minimize the cost of projects by grouping them and simultaneously finding the optimal balance between doing maintenance and renewal. We present a 0-1 pure integer linear programming that determines which projects should be performed together on which location and in which period (e.g., week or month). We consider railway track as a case for our study and test the performance of the proposed model on a set of test problems. The experimental results show that the proposed approach performs well.

Keywords: maintenance, renewal, scheduling, mathematical programming model

Procedia PDF Downloads 664

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

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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 consumption to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipment's 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, firstly, per dwelling, and secondly, at the level of a residential complex.

Keywords: smart grid, energy box, scheduling, Gang Model, energy consumption, energy management system, wireless sensor network

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Authors: Abdel-Aziz M. Mohamed

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This paper presents a state-of-the-art survey of the operations research models developed for internal audit planning. Two alternative approaches have been followed in the literature for audit planning: (1) identifying the optimal audit frequency; and (2) determining the optimal audit resource allocation. The first approach identifies the elapsed time between two successive audits, which can be presented as the optimal number of audits in a given planning horizon, or the optimal number of transactions after which an audit should be performed. It also includes the optimal audit schedule. The second approach determines the optimal allocation of audit frequency among all auditable units in the firm. In our review, we discuss both the deterministic and probabilistic models developed for audit planning. In addition, game theory models are reviewed to find the optimal auditing strategy based on the interactions between the auditors and the clients.

Keywords: operations research applications, audit frequency, audit-staff scheduling, audit planning

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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: real-time system (RTS), time utility function/ utility accrual (TUF/UA) scheduling, backward recovery mechanism, multiprocessor, discrete event simulation (DES)

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Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

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Authors: P. Kanakasabapathy, S. Radhika

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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, self-scheduling, sliding window technique

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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: Niyongabo Elyse

Abstract:

Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: C. E. Nugraheni, L. Abednego

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This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as meta-heuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: hyper-heuristics, evolutionary algorithms, production scheduling, meta-heuristic

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Authors: Eldho Paul, Brijesh Paul

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This work proposes an auction mechanism based solution methodology for the optimum scheduling of trucks in a cross-docking centre. The cross-docking centre is an important element of lean supply chain. It reduces the amount of storage and transportation costs in the distribution system compared to an ordinary warehouse. Better scheduling of trucks in a cross-docking center is the best way to reduce storage and transportation costs. Auction mechanism is commonly used for allocation of limited resources in different real-life applications. Here, we try to schedule inbound trucks by integrating auction mechanism with the functioning of a cross-docking centre. A mathematical model is developed for the optimal scheduling of inbound trucks based on the auction methodology. The determination of exact solution for problems involving large number of trucks was found to be computationally difficult, and hence a genetic algorithm based heuristic methodology is proposed in this work. A comparative study of exact and heuristic solutions is done using five classes of data sets. It is observed from the study that the auction-based mechanism is capable of providing good solutions to scheduling problem in cross-docking centres.

Keywords: auction mechanism, cross-docking centre, genetic algorithm, scheduling of trucks

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Authors: D. Dorota

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This paper presents a method to generate and schedule task in the architecture of embedded systems based on the simulated annealing. This method takes into account the attribute of divisibility of tasks. A proposal represents the process in the form of trees. Despite the fact that the architecture of Network-on-Chip (NoC) is an interesting alternative to a bus architecture based on multi-processors systems, it requires a lot of work that ensures the optimization of communication. This paper proposes an effective approach to generate dedicated NoC topology solving communication problems. Network NoC is generated taking into account the energy consumption and resource issues. Ultimately generated is minimal, dedicated NoC topology. The proposed solution is assumed to be a simple router design and the minimum number of lines.

Keywords: Network-on-Chip, NoC-based embedded systems, scheduling task in embedded systems, simulated annealing

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Authors: Khaled Moh. Alhamad

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This paper describes a tabu search heuristic for a ship routing and scheduling problem (SRSP). The method was developed to address the problem of loading cargos for many customers using heterogeneous vessels. Constraints relate to delivery time windows imposed by customers, the time horizon by which all deliveries must be made and vessel capacities. The results of a computational investigation are presented. Solution quality and execution time are explored with respect to problem size and parameters controlling the tabu search such as tenure and neighbourhood size.

Keywords: heuristic, scheduling, tabu search, transportation

Procedia PDF Downloads 478

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: John M. Ikome

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In the process of manufacturing, a machine breakdown usually forces a modified flow shop out of the prescribed state, this strategy reschedules part of the initial schedule to match up with the pre-schedule at some point with the objective to create a schedule that is reliable with the other production planning decisions like material flow, production and suppliers by utilizing a critical decision-making concept. We propose a rescheduling strategy and a match-up point that will have a determination procedure through an advanced feedback control mechanism to increase both the schedule quality and stability. These approaches are compared with alternative re-scheduling methods under different experimental settings.

Keywords: scheduling, heuristics, branch, integrated

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Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

Procedia PDF Downloads 323

Authors: Manan’Iarivo Rasolonjanahary, Chris Bingham, Nigel Schofield, Masoud Bazargan

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This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.

Keywords: model predictive control, non-scheduled, power limited sources, scheduled and stop-start battery charging

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

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Authors: Christian Meinecke, Bernd Scholz-Reiter

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The integrated problem of production and distribution scheduling is relevant in many industrial applications. Thus, many heuristics to solve this integrated problem have been developed in the last decade. Most of these heuristics use a sequential working principal or a single decomposition and integration approach to separate and solve sub-problems. A heuristic using a multi-step decomposition and integration approach is presented in this paper and evaluated in a case study. The result show significant improved results compared with sequential scheduling heuristics.

Keywords: production and outbound distribution, integrated planning, heuristic, decomposition, integration

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Authors: Geetha Baskaran, Andrzej Barjiela, Rong Qu

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Motivation: Nurse scheduling is a complex combinatorial optimization problem. It is also known as NP-hard. It needs an efficient re-scheduling to minimize some trade-off of the measures of violation by reducing selected constraints to soft constraints with measurements of their violations. Problem Statement: In this paper, we extend our novel approach to solve the nurse scheduling problem by transforming it through Information Granulation. Approach: This approach satisfies the rules of a typical hospital environment based on a standard benchmark problem. Generating good work schedules has a great influence on nurses' working conditions which are strongly related to the level of a quality health care. Domain transformation that combines the strengths of operation research and artificial intelligence was proposed for the solution of the problem. Compared to conventional methods, our approach involves judicious grouping (information granulation) of shifts types’ that transforms the original problem into a smaller solution domain. Later these schedules from the smaller problem domain are converted back into the original problem domain by taking into account the constraints that could not be represented in the smaller domain. An Integer Programming (IP) package is used to solve the transformed scheduling problem by expending the branch and bound algorithm. We have used the GNU Octave for Windows to solve this problem. Results: The scheduling problem has been solved in the proposed formalism resulting in a high quality schedule. Conclusion: Domain transformation represents departure from a conventional one-shift-at-a-time scheduling approach. It offers an advantage of efficient and easily understandable solutions as well as offering deterministic reproducibility of the results. We note, however, that it does not guarantee the global optimum.

Keywords: domain transformation, nurse scheduling, information granulation, artificial intelligence, simulation

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Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

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

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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: process planning, weighted scheduling, weighted due-date assignment, simulated annealing, evolutionary strategies, hybrid searches

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Authors: Nicole V. Shifrin

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Scheduling flexibility is becoming an increasingly available option for employees struggling to balance their work and life responsibilities, allowing employees to coordinate work schedules with their additional roles. The goal of such opportunities is to help employees manage the demands they face across domains of life by allowing employees to work from home, design their own work hours, take time off when necessary, along with various other scheduling accommodations. Organizations are also turning to utilizing scheduling flexibility to facilitate employee health and wellbeing through the reduction of stress and maximization of efficiency. The purpose of the present study is to investigate the effects of scheduling flexibility on employee health-related behaviors and outcomes through a synthesis of research. The current meta-analytic review of 19 samples within 16 studies with a total sample size of 20,707 employees examines the relationship between the degree of scheduling flexibility available to employees and the resulting health outcomes and exercise habits. The results demonstrate that reduced scheduling flexibility is associated with poorer health status, suggesting that schedule inflexibility can hinder employees’ ability to maintain and support their health. These findings hold practical implications for developing work schedules to promote employee health and health-related behaviors, such as eating well and exercising. Additionally, there was a positive association between increased scheduling flexibility and engagement in exercise, suggesting that employees with more flexible schedules exercise more frequently than those with less flexible schedules. A potential explanation for the resulting relationship is that flexible schedules leave employees more time due to shorter work days, shorter or eliminated commutes, etc. with which they can use to engage in healthy behaviors. These findings stress the importance of promoting job designs that facilitate employee engagement in healthy behaviors, which directly impact their overall health status. Implications for practice are discussed as well as future directions in examining the link between job design and employee health and well-being.

Keywords: exercise, health, meta-analysis, job design, scheduling flexibility

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Authors: Aayushi Patidar, Nishant Parihar

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One of the principal causes of failure in existing vehicle brokerage solutions is that they require the introduction of a single trusted third party to whom transport offers and requirements are sent, and which solves the scheduling problem. Advances in planning and scheduling could be utilized to address the scalability issues inherent here, but such refinements do not address the key need to decentralize decision-making. This is not to say that matchmaking of potential transport suppliers to consumers is not essential, but information from such a service should inform rather than determining the transport options for customers. The approach that is proposed, is the use of intelligent commuters that act within the system and to identify options open to users, weighing the evidence for desirability of each option given a model of the user’s priorities, and to drive dialogue among commuters in aiding users to solve their individual (or collective) transport goals. Existing research in commuter support for transport resource management has typically been focused on the provider. Our vision is to explore both the efficient use of limited transport resources and also to support the passengers in the transportation flexibility & integration among various modes in India.

Keywords: flexibility, integration, service design, technology

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