758 resultados para SCHEDULES


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At head of title: 97th Congress, 2d Session, House of Representatives, report no. 97-433.

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Inscriptions: Verso: [stamped] Photograph by Freda Leinwand. [463 West Street, Studio 229G, New York, NY 10014].

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We examine how using information on unconstrained demand can improve operational decisions. Specifically, we examine the widespread problem of developing course schedules in not-for-profit university settings. We investigate the potential benefit of incorporating, into the scheduling process, information on the unconstrained demand of students for courses. Prior to this study, the status quo in our college, like that in a large proportion of university settings, was building the course schedule to avoid time conflicts between required courses and to minimize time conflicts between designated groups of courses, such as electives in a particular area. Compared to the status quo approach, we find that, based on three semester's worth of actual data, an approach that explicitly considers students’ course preferences improves a student-based metric of schedule quality on the order of over 4% (which is the equivalent, in our setting, of improving service for over 20% of students).

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The main aim of radiotherapy is to deliver a dose of radiation that is high enough to destroy the tumour cells while at the same time minimising the damage to normal healthy tissues. Clinically, this has been achieved by assigning a prescription dose to the tumour volume and a set of dose constraints on critical structures. Once an optimal treatment plan has been achieved the dosimetry is assessed using the physical parameters of dose and volume. There has been an interest in using radiobiological parameters to evaluate and predict the outcome of a treatment plan in terms of both a tumour control probability (TCP) and a normal tissue complication probability (NTCP). In this study, simple radiobiological models that are available in a commercial treatment planning system were used to compare three dimensional conformal radiotherapy treatments (3D-CRT) and intensity modulated radiotherapy (IMRT) treatments of the prostate. Initially both 3D-CRT and IMRT were planned for 2 Gy/fraction to a total dose of 60 Gy to the prostate. The sensitivity of the TCP and the NTCP to both conventional dose escalation and hypo-fractionation was investigated. The biological responses were calculated using the Källman S-model. The complication free tumour control probability (P+) is generated from the combined NTCP and TCP response values. It has been suggested that the alpha/beta ratio for prostate carcinoma cells may be lower than for most other tumour cell types. The effect of this on the modelled biological response for the different fractionation schedules was also investigated.

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In architecture courses, instilling a wider understanding of the industry specific representations practiced in the Building Industry is normally done under the auspices of Technology and Science subjects. Traditionally, building industry professionals communicated their design intentions using industry specific representations. Originally these mainly two dimensional representations such as plans, sections, elevations, schedules, etc. were produced manually, using a drawing board. Currently, this manual process has been digitised in the form of Computer Aided Design and Drafting (CADD) or ubiquitously simply CAD. While CAD has significant productivity and accuracy advantages over the earlier manual method, it still only produces industry specific representations of the design intent. Essentially, CAD is a digital version of the drawing board. The tool used for the production of these representations in industry is still mainly CAD. This is also the approach taken in most traditional university courses and mirrors the reality of the situation in the building industry. A successor to CAD, in the form of Building Information Modelling (BIM), is presently evolving in the Construction Industry. CAD is mostly a technical tool that conforms to existing industry practices. BIM on the other hand is revolutionary both as a technical tool and as an industry practice. Rather than producing representations of design intent, BIM produces an exact Virtual Prototype of any building that in an ideal situation is centrally stored and freely exchanged between the project team. Essentially, BIM builds any building twice: once in the virtual world, where any faults are resolved, and finally, in the real world. There is, however, no established model for learning through the use of this technology in Architecture courses. Queensland University of Technology (QUT), a tertiary institution that maintains close links with industry, recognises the importance of equipping their graduates with skills that are relevant to industry. BIM skills are currently in increasing demand throughout the construction industry through the evolution of construction industry practices. As such, during the second half of 2008, QUT 4th year architectural students were formally introduced for the first time to BIM, as both a technology and as an industry practice. This paper will outline the teaching team’s experiences and methodologies in offering a BIM unit (Architectural Technology and Science IV) at QUT for the first time and provide a description of the learning model. The paper will present the results of a survey on the learners’ perspectives of both BIM and their learning experiences as they learn about and through this technology.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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The construction industry is categorised as being an information-intensive industry and described as one of the most important industries in any developed country, facing a period of rapid and unparalleled change (Industry Science Resources 1999) (Love P.E.D., Tucker S.N. et al. 1996). Project communications are becoming increasingly complex, with a growing need and fundamental drive to collaborate electronically at project level and beyond (Olesen K. and Myers M.D. 1999; Thorpe T. and Mead S. 2001; CITE 2003). Yet, the industry is also identified as having a considerable lack of knowledge and awareness about innovative information and communication technology (ICT) and web-based communication processes, systems and solutions which may prove beneficial in the procurement, delivery and life cycle of projects (NSW Government 1998; Kajewski S. and Weippert A. 2000). The Internet has debatably revolutionised the way in which information is stored, exchanged and viewed, opening new avenues for business, which only a decade ago were deemed almost inconceivable (DCITA 1998; IIB 2002). In an attempt to put these ‘new avenues of business’ into perspective, this report provides an overall ‘snapshot’ of current public and private construction industry sector opportunities and practices in the implementation and application of web-based ICT tools, systems and processes (e-Uptake). Research found that even with a reserved uptake, the construction industry and its participating organisations are making concerted efforts (fortunately with positive results) in taking up innovative forms of doing business via the internet, including e-Tendering (making it possible to manage the entire tender letting process electronically and online) (Anumba C.J. and Ruikar K. 2002; ITCBP 2003). Furthermore, Government (often a key client within the construction industry),and with its increased tendency to transact its business electronically, undoubtedly has an effect on how various private industry consultants, contractors, suppliers, etc. do business (Murray M. 2003) – by offering a wide range of (current and anticipated) e-facilities / services, including e-Tendering (Ecommerce 2002). Overall, doing business electronically is found to have a profound impact on the way today’s construction businesses operate - streamlining existing processes, with the growth in innovative tools, such as e-Tender, offering the construction industry new responsibilities and opportunities for all parties involved (ITCBP 2003). It is therefore important that these opportunities should be accessible to as many construction industry businesses as possible (The Construction Confederation 2001). Historically, there is a considerable exchange of information between various parties during a tendering process, where accuracy and efficiency of documentation is critical. Traditionally this process is either paper-based (involving large volumes of supporting tender documentation), or via a number of stand-alone, non-compatible computer systems, usually costly to both the client and contractor. As such, having a standard electronic exchange format that allows all parties involved in an electronic tender process to access one system only via the Internet, saves both time and money, eliminates transcription errors and increases speed of bid analysis (The Construction Confederation 2001). Supporting this research project’s aims and objectives, researchers set to determine today’s construction industry ‘current state-of-play’ in relation to e-Tendering opportunities. The report also provides brief introductions to several Australian and International e-Tender systems identified during this investigation. e-Tendering, in its simplest form, is described as the electronic publishing, communicating, accessing, receiving and submitting of all tender related information and documentation via the internet, thereby replacing the traditional paper-based tender processes, and achieving a more efficient and effective business process for all parties involved (NT Governement 2000; NT Government 2000; NSW Department of Commerce 2003; NSW Government 2003). Although most of the e-Tender websites investigated at the time, maintain their tendering processes and capabilities are ‘electronic’, research shows these ‘eTendering’ systems vary from being reasonably advanced to more ‘basic’ electronic tender notification and archiving services for various industry sectors. Research also indicates an e-Tender system should have a number of basic features and capabilities, including: • All tender documentation to be distributed via a secure web-based tender system – thereby avoiding the need for collating paperwork and couriers. • The client/purchaser should be able to upload a notice and/or invitation to tender onto the system. • Notification is sent out electronically (usually via email) for suppliers to download the information and return their responses electronically (online). • During the tender period, updates and queries are exchanged through the same e-Tender system. • The client/purchaser should only be able to access the tenders after the deadline has passed. • All tender related information is held in a central database, which should be easily searchable and fully audited, with all activities recorded. • It is essential that tender documents are not read or submitted by unauthorised parties. • Users of the e-Tender system are to be properly identified and registered via controlled access. In simple terms, security has to be as good as if not better than a manual tender process. Data is to be encrypted and users authenticated by means such as digital signatures, electronic certificates or smartcards. • All parties must be assured that no 'undetected' alterations can be made to any tender. • The tenderer should be able to amend the bid right up to the deadline – whilst the client/purchaser cannot obtain access until the submission deadline has passed. • The e-Tender system may also include features such as a database of service providers with spreadsheet-based pricing schedules, which can make it easier for a potential tenderer to electronically prepare and analyse a tender. Research indicates the efficiency of an e-Tender process is well supported internationally, with a significant number, yet similar, e-Tender benefits identified during this investigation. Both construction industry and Government participants generally agree that the implementation of an automated e-Tendering process or system enhances the overall quality, timeliness and cost-effectiveness of a tender process, and provides a more streamlined method of receiving, managing, and submitting tender documents than the traditional paper-based process. On the other hand, whilst there are undoubtedly many more barriers challenging the successful implementation and adoption of an e-Tendering system or process, researchers have also identified a range of challenges and perceptions that seem to hinder the uptake of this innovative approach to tendering electronically. A central concern seems to be that of security - when industry organisations have to use the Internet for electronic information transfer. As a result, when it comes to e-Tendering, industry participants insist these innovative tendering systems are developed to ensure the utmost security and integrity. Finally, if Australian organisations continue to explore the competitive ‘dynamics’ of the construction industry, without realising the current and future, trends and benefits of adopting innovative processes, such as e-Tendering, it will limit their globalising opportunities to expand into overseas markets and allow the continuation of international firms successfully entering local markets. As such, researchers believe increased knowledge, awareness and successful implementation of innovative systems and processes raises great expectations regarding their contribution towards ‘stimulating’ the globalisation of electronic procurement activities, and improving overall business and project performances throughout the construction industry sectors and overall marketplace (NSW Government 2002; Harty C. 2003; Murray M. 2003; Pietroforte R. 2003). Achieving the successful integration of an innovative e-Tender solution with an existing / traditional process can be a complex, and if not done correctly, could lead to failure (Bourn J. 2002).

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The art of storytelling is one of the oldest forms of creative discourse. Apart from finding stories, the most important job in television is the construction of stories to have a broad audience appeal. This first-hand review of Missing Persons Unit, hereafter referred to as MPU, a prime time program on the Nine Network in Australia with immense audience appeal, is an original work by the executive producer (development and series producer Series One, executive producer Series Two and Three) based on an overview of two-and-a-half years of production on three series. Through a case study approach, this Masters project explores how story is constructed into a television format. The thesis comprises two parts: the creative component (weighted 50%) is demonstrated through two programs of MPU (one program for evaluation) and the academic component through a written exegesis (50%). This case study aims to demonstrate how observational hybrid series such as MPU can be managed to quick turn-around schedules with precise skill sets that cut across a number of traditional genre styles. With the advent of radio and then television, storytelling found a home and a series of labels called genres to help place them in a schedule for listeners and viewers to choose. Over recent years, with the advent of digital technology and the rush to collect the masses of content required to feed the growing television slate, storytelling has often been replaced by story gathering. Today even in factual series where a clear story construct is important, third party ‘quick fix’ specialists are hired to shape raw content shot by a field team, who never put their own work together and may never come into the edit suite during a project. This thesis explores the art of storytelling in fast turn-around television. In particular it explores the layer cake approach used in the production process of MPU, that enables producers of fast turn-around television to shepherd their own stories from field through to post-production. While each new hybrid series will require its own particular sets of skills, the exploration of the genesis of MPU will demonstrate the building blocks required to successfully produce this type of factual series. This study is also intended as a ‘road map’ for producers who wish to develop similar series.

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Online scheduling is considered in this paper for the Operating Theatre. Robust elective schedules are determined in the offline environment prior to the day of surgery for the online environment. Changes to the offline schedule during project implementation are minimized using an online scheduling model that operates in real-time. The model aims to minimise cancellations of pre-scheduled elective patients whilst also allowing for additional scheduling of emergency cases, time permitting, which may arise during the schedules implementation. Surgical durations are modelled with a lognormal distribution. The single theatre case is solved and the computationally complex multiple theatre case, which is left for future work, is discussed.

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Purpose: The aim of this study was to characterize the clinical signs, symptoms, and ocular and systemic comorbidities in a large case series of contact lens-related microbial keratitis. Methods: Two hundred ninety-seven cases of contact lens-related microbial keratitis, aged between 15 and 64 years were detected through surveillance of hospital and community based ophthalmic practitioners in Australia and New Zealand. Full clinical data were available for 190 cases and 90 were interviewed by telephone. Clinical data included the size, location, and degree of anterior chamber response. Symptom data were available from the practitioner and from participant self-report. Associations between symptoms and disease severity were evaluated. Data on ocular and systemic disease were collected from participants and practitioners. The frequency of comorbidities was compared between the different severities of disease and to population norms. Results: More severe disease was associated with greater symptom severity and pain was the most prevalent symptom reported. Ninety-one percent of cases showed progression of ocular symptoms after lens removal, and symptom progression was associated with all severities of disease. Twenty-five percent of cases reported prior episodes requiring emergency attention. Thyroid disease (p 0.05) and self-reported poor health (p 0.001) were more common in cases compared with age-matched population norms. Discussion: Information on the signs, symptoms, and comorbidities associated with contact lens-related microbial keratitis may be useful in patient education and for practitioners involved in the fitting of lenses and management of complications. Although pain was the most common symptom experienced, progression of symptoms despite lens removal was close to universal. Poor general health, particularly respiratory disease and thyroid disease was more common in cases than in the general population, which may prompt practitioners to recommend flexibility in wear schedules when in poor health or the selection of a lower risk wear schedule in at risk patients

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In this paper we describe the recent development of a low-bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second. © 2007 IEEE.

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Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.