Search results for: workflow scheduling

Authors: P. Hooshangitabrizi, I. Contreras, N. Bhuiyan

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This work presents an online scheduling problem which accommodates multiple requests of patients for chemotherapy treatments in a cancer center of a major metropolitan hospital in Canada. To solve the problem, an adaptive flexible approach is proposed which systematically combines two optimization models. The first model is intended to dynamically schedule arriving requests in the form of waiting lists whereas the second model is used to reschedule the already booked patients with the goal of finding better resource allocations when new information becomes available. Both models are created as mixed integer programming formulations. Various controllable and flexible parameters such as deviating the prescribed target dates by a pre-determined threshold, changing the start time of already booked appointments and the maximum number of appointments to move in the schedule are included in the proposed approach to have sufficient degrees of flexibility in handling arrival requests and unexpected changes. Several computational experiments are conducted to evaluate the performance of the proposed approach using historical data provided by the oncology clinic. Our approach achieves outstandingly better results as compared to those of the scheduling system being used in practice. Moreover, several analyses are conducted to evaluate the effect of considering different levels of flexibility on the obtained results and to assess the performance of the proposed approach in dealing with last-minute changes. We strongly believe that the proposed flexible adaptive approach is very well-suited for implementation at the clinic to provide better patient-care services and to utilize available resource more efficiently.

Keywords: chemotherapy scheduling, multi-appointment modeling, optimization of resources, satisfaction of patients, mixed integer programming

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Authors: Salman Ali Nisar, Suzuki Koji

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In this paper we developed a new algorithm to convert the project scheduling time into calendar date in order to handle non-interruptible activities not to be split by non-working days (such as weekend and holidays). In a construction project some activities might require not to be interrupted even on non-working days, or to be finished on the end day of business days. For example, concrete placing work might be required to be completed by the end day of weekdays i.e. Friday, and curing in the weekend. This research provides an algorithm that imposes time constraint for start and finish times of non-interruptible activities. The algorithm converts working days, which is obtained by Critical Path Method (CPM), to calendar date with consideration of the start date of a project. After determining the interruption by non-working days, the start time of a certain activity should be postponed, if there is enough total float value. Otherwise, the duration is shortened by hiring additional resources capacity or/and using overtime work execution. Then, time constraints are imposed to start time and finish time of the activity. The algorithm is developed in Excel Spreadsheet for microcomputer and therefore we can easily get a feasible, calendared construction schedule for such a construction project with some non-interruptible activities.

Keywords: project management, scheduling, critical path method, time constraint, non-interruptible tasks

Procedia PDF Downloads 496

Authors: Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kokcam, Mumtaz Ipek

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Process planning, scheduling, and due date assignment are three important manufacturing functions which are studied independently in literature. There are hundreds of works on IPPS and SWDDA problems but a few works on IPPSDDA problem. Integrating these three functions is very crucial due to the high relationship between them. Since the scheduling problem is in the NP-Hard problem class without any integration, an integrated problem is even harder to solve. This study focuses on the integration of these functions. Sum of weighted tardiness, earliness, and due date related costs are used as a penalty function. Random search and hybrid metaheuristics are used to solve the integrated problem. Marginal improvement in random search is very high in the early iterations and reduces enormously in later iterations. At that point directed search contribute to marginal improvement more than random search. In this study, random and genetic search methods are combined to find better solutions. Results show that overall performance becomes better as the integration level increases.

Keywords: process planning, genetic algorithm, hybrid search, random search, weighted due-date assignment, weighted scheduling

Procedia PDF Downloads 359

Authors: J. Ikome, M. Ndeley

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When a machine breakdown forces a Modified Flow Shop (MFS) out of the prescribed state, the proposed strategy reschedules part of the initial schedule to match up with the preschedule at some point. The objective is to create a new schedule that is consistent with the other production planning decisions like material flow, tooling and purchasing by utilizing the time critical decision making concept. We propose a new rescheduling strategy and a match-up point determination procedure through a feedback mechanism to increase both the schedule quality and stability. The proposed approach is compared with alternative reactive scheduling methods under different experimental settings.

Keywords: advanced critical task methods modified flow shop (MFS), Manufacturing, experiment, determination

Procedia PDF Downloads 403

Authors: M. Ndeley

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Now our days, Almost all manufacturing facilities need to use production planning and scheduling systems to increase productivity and to reduce production costs. Real-life production operations are subject to a large number of unexpected disruptions that may invalidate the original schedules. In these cases, rescheduling is essential to minimize the impact on the performance of the system. In this work we consider flow shop layouts that have seldom been studied in the rescheduling literature. We generate and employ three types of disruption that interrupt the original schedules simultaneously. We develop rescheduling algorithms to finally accomplish the twofold objective of establishing a standard framework on the one hand; and proposing rescheduling methods that seek a good trade-off between schedule quality and stability on the other.

Keywords: flow shop scheduling, uncertainty, rescheduling, stability

Procedia PDF Downloads 436

Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

Procedia PDF Downloads 318

Authors: Martha E. Ndeley

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Operation management is the key element within the manufacturing process. However, during this process, there are a number of unforeseen disruptions that causes the process to a standstill which are, machine breakdown, employees absenteeism, improper scheduling. When this happens, it forces the shop flow to a rescheduling process and these strategy reschedules only a limited part of the initial schedule to match up with the pre-schedule at some point with the objective to create a new schedule that is reliable which in the long run gets disrupted. In this work, we have developed feedback control system that minimizes any form of disruption before the impact becomes severe, the model was tested in a paper manufacturing industries and the results revealed that, if the disruption is minimized at the initial state, the impact becomes unnoticeable.

Keywords: disruption, machine, absenteeism, scheduling

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Authors: Thomas Yeboah

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Cloud Computing is newly paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). As Cloud Computing is a newly style of computing on the internet. It has many merits along with some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the load balancing, fault tolerance and different security issues in cloud environment.In this paper the main concern is to develop an effective load balancing algorithm that gives satisfactory performance to both, cloud users and providers. This proposed algorithm (hybrid Bee Ant Colony algorithm) is a combination of two dynamic algorithms: Ant Colony Optimization and Bees Life algorithm. Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues whiles the Bees Life algorithm is used for optimization of job scheduling in cloud environment. The results of the proposed algorithm shows that the hybrid Bee Ant Colony algorithm outperforms the performances of both Ant Colony algorithm and Bees Life algorithm when evaluated the proposed algorithm performances in terms of Waiting time and Response time on a simulator called CloudSim.

Keywords: ant colony optimization algorithm, bees life algorithm, scheduling algorithm, performance, cloud computing, load balancing

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Authors: Martin Georgiev, Milena Nanova, Damyan Damov

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Architects, engineers, and developers need to analyse and implement a wide spectrum of data in different formats, if they want to produce viable residential developments. Usually, this data comes from a number of different sources and is not well structured. The main objective of this research project is to provide parametric tools working with real geodesic data that can generate residential solutions. Various codes, regulations and design constraints are described by variables and prioritized. In this way, we establish a common workflow for architects, geodesists, and other professionals involved in the building and investment process. This collaborative medium ensures that the generated design variants conform to various requirements, contributing to a more streamlined and informed decision-making process. The quantification of distinctive characteristics inherent to typical residential structures allows a systematic evaluation of the generated variants, focusing on factors crucial to designers, such as daylight simulation, circulation analysis, space utilization, view orientation, etc. Integrating real geodesic data offers a holistic view of the built environment, enhancing the accuracy and relevance of the design solutions. The use of generative algorithms and parametric models offers high productivity and flexibility of the design variants. It can be implemented in more conventional CAD and BIM workflow. Experts from different specialties can join their efforts, sharing a common digital workspace. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the building investment during its entire lifecycle.

Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization

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Authors: Danilo Di Donato

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The continuous new releases of free and open source software (FOSS) and the high costs of proprietary software -whose monopoly is characterized by closed codes and the low level of implementation and customization of software by end-users- impose a reflection on possible tools that can be chosen and adopted for the design and the representation of new steel constructions. The paper aims to show experimentation carried out to verify the actual potential and the effective applicability of FOSS supports to the BIM modeling of steel structures, particularly considering the goal of a possible workflow in order to achieve high level of development (LOD); allow effective interchange methods between different software. To this end, the examined software packages are those with open source or freeware licenses, in order to evaluate their use in architectural praxis. The test has primarily involved the experimentation of Freecad -the only Open Source software that allows a complete and integrated BIM workflow- and then the results have been compared with those of two proprietary software, Sketchup and TeklaBim Sight, which are released with a free version, but not usable for commercial purposes. The experiments carried out on Open Source, and freeware software was then compared with the outcomes that are obtained by two proprietary software, Sketchup Pro and Tekla Structure which has special modules particularly addressed to the design of steel structures. This evaluation has concerned different comparative criteria, that have been defined on the basis of categories related to the reliability, the efficiency, the potentiality, achievable LOD and user-friendliness of the analyzed software packages. In order to verify the actual outcomes of FOSS BIM for the steel structure projects, these results have been compared with a simulation related to a real case study and carried out with a proprietary software BIM modeling. Therefore, the same design theme, the project of a shelter of public space, has been developed using different software. Therefore the purpose of the contribution is to assess what are the developments and potentialities inherent in FOSS BIM, in order to estimate their effective applicability to professional practice, their limits and new fields of research they propose.

Keywords: BIM, steel buildings, FOSS, LOD

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Authors: Rudolph Carl Barrientos, Juwaln Diego Descallar, Rainer James Palmiano

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Household Appliance Scheduling Systems (HASS) coupled with a Time-of-Use (TOU) pricing scheme, a form of Demand Side Management (DSM), is not widely utilized in the Philippines’ residential electricity sector. This paper’s goal is to encourage distribution utilities (DUs) to adopt HASS and TOU by analyzing the effect of household schedulers on the electricity price and load profile in a residential environment. To establish this, a city based on an implemented survey is generated using Monte Carlo Analysis (MCA). Then, a Binary Particle Swarm Optimization (BPSO) algorithm-based HASS is developed considering user satisfaction, electricity budget, appliance prioritization, energy storage systems, solar power, and electric vehicles. The simulations were assessed under varying levels of user compliance. Results showed that the average electricity cost, peak demand, and peak-to-average ratio (PAR) of the city load profile were all reduced. Therefore, the deployment of the HASS and TOU pricing scheme is beneficial for both stakeholders.

Keywords: appliance scheduling, DSM, TOU, BPSO, city-wide simulation, electric vehicle, appliance prioritization, energy storage system, solar power

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Authors: Zaid Jamal Saeed Almahmoud

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Smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing peak power consumption under a fixed delay requirement is a significant problem in the smart grid.For this problem, all appliances must be scheduled within a given finite time duration. We consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-hard, we analyze the performance of a version of the natural greedy heuristic for solving this problem. Our theoretical analysis and experimental results show that the proposed heuristic outperforms existing methods by providing a better approximation to the optimal solution.

Keywords: peak demand scheduling, approximation algorithms, smart grid, heuristics

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Authors: Sanjay Kumar Parjapati, Ajai Jain

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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times

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Authors: Wlodzimierz Ogryczak, Tomasz Sliwinski, Jaroslaw Hurkala, Mariusz Kaleta, Bartosz Kozlowski, Piotr Palka

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Implementation concepts of a decision support system for planning and management of mobile personnel tasks (sales representatives and others) are discussed. Large-scale periodic time-dependent vehicle routing and scheduling problems with complex constraints are solved for this purpose. Complex nonuniform constraints with respect to frequency, time windows, working time, etc. are taken into account with additional fast adaptive procedures for operational rescheduling of plans in the presence of various disturbances. Five individual solution quality indicators with respect to a single personnel person are considered. This paper deals with modeling issues corresponding to the problem and general solution concepts. The research was supported by the European Union through the European Regional Development Fund under the Operational Programme ‘Innovative Economy’ for the years 2007-2013; Priority 1 Research and development of modern technologies under the project POIG.01.03.01-14-076/12: 'Decision Support System for Large-Scale Periodic Vehicle Routing and Scheduling Problems with Complex Constraints.'

Keywords: mobile personnel management, multiple criteria, time dependent, time windows, vehicle routing and scheduling

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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: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

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Authors: Kunal Das, Priya Sengupta, Abhishek K. Singh

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Pin assignment, scheduling, routing and error detection for arbitrary biochemical protocols in Digital Microfluidic Biochip have been reported in this paper. The research work is concentrating on pin assignment for 2 or 3 droplets routing in the arbitrary biochemical protocol, scheduling and routing in m × n biochip. The volumetric error arises due to droplet split in the biochip. The volumetric error detection is also addressed using biochip AND logic gate which is known as microfluidic AND or mAND gate. The algorithm for pin assignment for m × n biochip required m+n-1 numbers of pins. The basic principle of this algorithm is that no same pin will be allowed to be placed in the same column, same row and diagonal and adjacent cells. The same pin should be placed a distance apart such that interference becomes less. A case study also reported in this paper.

Keywords: digital microfludic biochip, cross-contamination, pin assignment, microfluidic AND gate

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Authors: Ekrem Canli, Thomas Glade

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The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

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Authors: Sumati Manchanda

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Cloud computing is one of the most recent developing engineering and is consistently utilized as a part of different IT firms so as to make benefits like expense sparing or financial minimization, it must be eco cordial also. In this manner, Green Cloud Computing is the need of the today's current situation. It is an innovation that is rising as data correspondence engineering. This paper surveys the unequivocal endeavors made by different specialists to make Cloud Computing more vitality preserving, to break down its vitality utilization focused around sorts of administrations gave furthermore to diminish the carbon foot shaped impression rate by colossal methodologies furthermore edify virtualization idea alongside different diverse methodologies which utilize virtual machines scheduling and migration. The summary of the proposed work by various authors that we have reviewed is also presented in the paper.

Keywords: cloud computing, green cloud computing, scheduling, migration, virtualization, energy efficiency

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Authors: Kwan Hee Han

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In today’s business environments, frequent change of customer requirements is a tough challenge to manufacturing company. To cope with these challenges, a production planning and scheduling (PP&S) function might be established to provide accountability for both customer service and operational efficiency. Nowadays, many manufacturing firms have utilized PP&S software solutions to generate a realistic production plan and schedule to adapt to external changes efficiently. However, companies which consider the introduction of PP&S software solution, still have difficulties for selecting adequate solution to meet their specific needs. Since the task of PP&S is the one of major building blocks of SCM (Supply Chain Management) architecture, which deals with short term decision making in the production process of SCM, it is needed that the functionalities of PP&S should be analysed within the whole SCM process. The aim of this paper is to analyse the PP&S functionalities and its system architecture from the SCM perspective by using the criteria of level of planning hierarchy, major 4 SCM processes and problem-solving approaches, and finally propose a classification framework of PP&S solutions to facilitate the comparison among various commercial software solutions. By using proposed framework, several major PP&S solutions are classified and positioned according to their functional characteristics in this paper. By using this framework, practitioners who consider the introduction of computerized PP&S solutions in manufacturing firms can prepare evaluation and benchmarking sheets for selecting the most suitable solution with ease and in less time.

Keywords: production planning, production scheduling, supply chain management, the advanced planning system

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Authors: Ahmed Al-Sultan

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The check-in area of airport terminal is one of the busiest sections at airports at certain periods. The passengers are subjected to queues and delays during the check-in process. These delays and queues are due to constraints in the capacity of service facilities. In this project, the airport terminal is decomposed into several check-in areas. The airport check-in scheduling problem requires both a deterministic (integer programming) and stochastic (simulation) approach. Integer programming formulations are provided to minimize the total number of counters in each check-in area under the realistic constraint that counters for one and the same flight should be adjacent and the desired number of counters remaining in each area should be fixed during check-in operations. By using simulation, the airport system can be modeled to study the effects of various parameters such as number of passengers on a flight and check-in counter opening and closing time.

Keywords: airport terminal, integer programming, scheduling, simulation

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Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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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: Niyongabo Elyse

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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: Markus Heck, Hans Vettiger

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Small and medium-sized enterprises (SME) are the backbone of central Europe’s economies and have a significant contribution to the gross domestic product. Production planning and scheduling (PPS) is still a crucial element in manufacturing industries of the 21st century even though this area of research is more than a century old. The topic of PPS is well researched especially in the context of large enterprises in the manufacturing industry. However, the implementation of PPS methodologies within SME is mostly unobserved. This work analyzes how PPS is implemented in SME with the geographical focus on Switzerland and its vicinity. Based on restricted resources compared to large enterprises, SME have to face different challenges. The real problem areas of selected enterprises in regards of PPS are identified and evaluated. For the identified real-life problem areas of SME clear and detailed recommendations are created, covering concepts and best practices and the efficient usage of PPS. Furthermore, the economic and entrepreneurial value for companies is lined out and why the implementation of the introduced recommendations is advised.

Keywords: central Europe, PPS, production planning, SME

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Authors: Adel Francis

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Most of scheduling methods and software apply the critical path logic. This logic schedule activities, apply constraints between these activities and try to optimize and level the allocated resources. The extensive use of this logic produces a complex an erroneous network hard to present, follow and update. Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic, and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. The objective of the space planning is to link the spatial and temporal aspects, promote efficient use of the site, define optimal site occupancy rates, and ensures suitable rotation of the workforce in the different spaces. The Chronographic scheduling modelling belongs to this category and models construction operations as well as their processes, logical constraints, association and organizational models, which help to better illustrate the schedule information using multiple flexible approaches. The model defined three categories of areas (punctual, surface and linear) and four different layers (space creation, systems, closing off space, finishing, and reduction of space). The Chronographical modelling is a more complete communication method, having the ability to alternate from one visual approach to another by manipulation of graphics via a set of parameters and their associated values. Each individual approach can help to schedule a certain project type or specialty. Visual communication can also be improved through layering, sheeting, juxtaposition, alterations, and permutations, allowing for groupings, hierarchies, and classification of project information. In this way, graphic representation becomes a living, transformable image, showing valuable information in a clear and comprehensible manner, simplifying the site management while simultaneously utilizing the visual space as efficiently as possible.

Keywords: building projects, chronographic modelling, CPM, critical path, precedence diagram, scheduling

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Authors: Zahra Majd, Mohsen Kalantar

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Power management and voltage regulation is one of the most important issues in microgrid (MG) control and scheduling. This paper proposes a multiobjective scheduling formulation that consists of active power costs, voltage fluctuations summation, and technical constraints of MG. Furthermore, load flow and reserve constraints are considered to achieve proper voltage regulation. A modified Jacobian matrix is presented for calculating voltage variations and Mont Carlo simulation is used for generating and reducing scenarios. To convert the problem to a mixed integer linear program, a linearization procedure for nonlinear equations is presented. The proposed model is applied to a typical low-voltage MG and two different cases are investigated. The results show the effectiveness of the proposed model.

Keywords: microgrid, energy management system, voltage fluctuations, modified Jacobian matrix

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Authors: Wuthichai Wongthatsanekorn, Nuntana Matheekrieangkrai

Abstract:

This research proposes Bee Algorithm (BA) to optimize Ready Mixed Concrete (RMC) truck scheduling problem from single batch plant to multiple construction sites. This problem is considered as an NP-hard constrained combinatorial optimization problem. This paper provides the details of the RMC dispatching process and its related constraints. BA was then developed to minimize total waiting time of RMC trucks while satisfying all constraints. The performance of BA is then evaluated on two benchmark problems (3 and 5construction sites) according to previous researchers. The simulation results of BA are compared in term of efficiency and accuracy with Genetic Algorithm (GA) and all problems show that BA approach outperforms GA in term of efficiency and accuracy to obtain optimal solution. Hence, BA approach could be practically implemented to obtain the best schedule.

Keywords: bee colony optimization, ready mixed concrete problem, ruck scheduling, multiple construction sites

Procedia PDF Downloads 381

Authors: Anastasios Charisis, Evangelos Kaisar, Steven Spana, Lili Du

Abstract:

Logistics play a vital role in the prosperity of today’s cities, but current urban logistics practices are proving problematic, causing negative effects such as traffic congestion and environmental impacts. This paper proposes an alternative urban logistics system, leasing hubs inside cities for designated time intervals, and using handcarts for last-mile deliveries. A mathematical model for selecting the locations of hubs and allocating customers, while also scheduling the optimal times during the day for leasing hubs is developed. The proposed model is compared to current delivery methods requiring door-to-door truck deliveries. It is shown that truck traveled distances decrease by more than 60%. In addition, analysis shows that in certain conditions the approach can be economically competitive and successfully applied to address real problems.

Keywords: hub location, last-mile, logistics, optimization

Procedia PDF Downloads 186