Job Shop Scheduling with Flexible Maintenance Planning

This thesis considers the scheduling challenges encountered at a particular facility in the nuclear industry. The scheduling problem is modelled as a variant of the job shop scheduling problem. Important aspects of the considered problem include the scheduling of jobs with both soft and hard due dates, and the integration of maintenance planning with job scheduling. Two variants of the scheduling problem are considered: The first variant makes the classic job shop assumption of infinite queueing capacity at each machine, while such queueing capacity is non-existent in the second variant. Without queueing capacity, the scheduling problem is a variant of the blocking job shop problem. For the non-blocking variant of the problem, it is shown that good solutions can be obtained quickly by hybridising a novel Ant Colony Optimisation method with a novel Branch and Bound method. For the blocking variant of the problem, it is shown that a novel Branch and Bound method can rapidly find optimal solutions. This Branch and Bound method is shown to provide good performance due to, amongst other things, a novel search strategy and a novel branching strategy

Development of a maintenance possession scheduler for a railway

Thesis (MEng)--Stellenbosch University, 2022.ENGLISH SUMMARY: Maintenance of rail infrastructure is an important element in rail operations in order to keep tra c moving. However, maintenance causes infrastructure to be taken out of service, which impacts tra c ow. In this study, the requirements of a maintenance possession scheduler for a South African application was investigated, and a proposed solution was subsequently developed. The main objective of the scheduler was to minimise the deviation of the train service on a subset of rail infrastructure while ensuring that the required maintenance is done. To achieve this, a literature study was done on a number of themes, which include an overview of the local railway operator with a look at the role of industrial engineering as a function in the railway operator business, railway infrastructure and operations, planning of railway operations, and maintenance in the context of rail operations. The topic of possession scheduling was then studied; the previous themes helped the researcher to learn the bigger picture while understanding possession scheduling is critical for this study. Past and recent works were studied and research areas and trends were synthesised, including time span of possession scheduling in optimisation models, and whether it was done on microscopic, mesoscopic or macroscopic level. The various optimisation objectives formulated by researchers were also noted, among other subthemes. An application case was identi ed as the railway infrastructure between Bellville and Wellington in the Western Cape province of South Africa. A novel mixed-integer linear programming model was formulated for this case and implemented in Cplex, after which it was validated. The model can do possession scheduling for 24 hours on a microscopic level. Finally, several experiments were conducted to investigate the performance and results of the model. It was found that the model delivered optimal results in less than eight minutes, which makes it a feasible maintenance possession scheduler for day-to-day work in the immediate planning horizon.AFRIKAANS OPSOMMING: Instandhouding van spoorinfrastruktuur is 'n belangrike element in spoorwegoperasies ten einde verkeervloei te verseker. Instandhouding veroorsaak egter dat infrastruktuur uit diens geneem word wat verkeer weer belemmer. In hierdie studie was die vereistes van 'n besitskeduleerder vir instandhouding vir 'n Suid-Afrikaanse toepassing ondersoek, en die voorgestelde oplossing was daarna ontwikkel. Die hoofdoelwit van die skeduleerder was om die afwykings van die trein diens te minimeer op 'n gedeelte van spoorinfrastruktuur terwyl verseker word dat die nodige instandhouding gedoen word. Om dit te bereik is 'n literatuurstudie op 'n aantal temas gedoen. Dit sluit in 'n oorsig van die plaaslike spoorwegoperateur en die rol wat bedryfsingenieurswese as funksie daarin vervul, spoorweginfrastruktuur en operasies, en instandhouding in die konteks van spoorwegoperasies. Die onderwerp van besitskedulering was daarna bestudeer; die vorige temas het die navorser gehelp om die groter prentjie te verstaan, terwyl die studie van besitskedulering kritiek was vir hierdie studie. Navorsingswerk uit die verlede asook onlangse werk was bestudeer en navorsingsareas en tendense is deur sintese bepaal. Dit sluit in die tydsduur van besitskedulering in optimeringsmodelle en of dit op mikro-, meso- of makroskopiese vlak gedoen word. Die verskillende optimeringsdoelwitte wat navorsers formuleer het is ook waargeneem, asook met ander subtemas. 'n Gevallestudie vir toepassing van 'n besitskeduleerder vir instandhouding is identi seer as die spoorweginfrastruktuur tussen Bellville enWellington in die Wes-Kaap provinsie van Suid-Afrika. 'n Nuwe gemengde heeltal-line^ere programmeringmodel was geformuleer vir hierdie gevallestudie en in Cplex implementeer, waarna dit gevalideer is. Die model kan besitskedulering vir 24 uur doen op mikrovlak. Verskeie eksperimente is uiteindelik uitgevoer om die prestasie en resultate van die model waar te neem. Dit is bevind dat die model optimale resultate in minder as agt minute kon lewer, wat dit 'n aanvaarbare instandhouding besitskeduleerder maak vir dag-tot-dag werk in die nabye beplanningshorison.Master

Modelling of interactions between rail service and travel demand: a passenger-oriented analysis

The proposed research is situated in the field of design, management and optimisation in railway network operations. Rail transport has in its favour several specific features which make it a key factor in public transport management, above all in high-density contexts. Indeed, such a system is environmentally friendly (reduced pollutant emissions), high-performing (high travel speeds and low values of headways), competitive (low unitary costs per seat-km or carried passenger-km) and presents a high degree of adaptability to intermodality. However, it manifests high vulnerability in the case of breakdowns. This occurs because a faulty convoy cannot be easily overtaken and, sometimes, cannot be easily removed from the line, especially in the case of isolated systems (i.e. systems which are not integrated into an effective network) or when a breakdown occurs on open tracks. Thus, re-establishing ordinary operational conditions may require excessive amounts of time and, as a consequence, an inevitable increase in inconvenience (user generalised cost) for passengers, who might decide to abandon the system or, if already on board, to exclude the railway system from their choice set for the future. It follows that developing appropriate techniques and decision support tools for optimising rail system management, both in ordinary and disruption conditions, would consent a clear influence of the modal split in favour of public transport and, therefore, encourage an important reduction in the externalities caused by the use of private transport, such as air and noise pollution, traffic congestion and accidents, bringing clear benefits to the quality of life for both transport users and non-users (i.e. individuals who are not system users). Managing to model such a complex context, based on numerous interactions among the various components (i.e. infrastructure, signalling system, rolling stock and timetables) is no mean feat. Moreover, in many cases, a fundamental element, which is the inclusion of the modelling of travel demand features in the simulation of railway operations, is neglected. Railway transport, just as any other transport system, is not finalised to itself, but its task is to move people or goods around, and, therefore, a realistic and accurate cost-benefit analysis cannot ignore involved flows features. In particular, considering travel demand into the analysis framework presents a two-sided effect. Primarily, it leads to introduce elements such as convoy capacity constraints and the assessment of dwell times as flow-dependent factors which make the simulation as close as possible to the reality. Specifically, the former allows to take into account the eventuality that not all passengers can board the first arriving train, but only a part of them, due to overcrowded conditions, with a consequent increase in waiting times. Due consideration of this factor is fundamental because, if it were to be repeated, it would make a further contribution to passengers’ discontent. While, as regards the estimate of dwell times on the basis of flows, it becomes fundamental in the planning phase. In fact, estimating dwell times as fixed values, ideally equal for all runs and all stations, can induce differences between actual and planned operations, with a subsequent deterioration in system performance. Thus, neglecting these aspects, above all in crowded contexts, would render the simulation distorted, both in terms of costs and benefits. The second aspect, on the other hand, concerns the correct assessment of effects of the strategies put in place, both in planning phases (strategic decisions such as the realisation of a new infrastructure, the improvement of the current signalling system or the purchasing of new rolling stock) and in operational phases (operational decisions such as the definition of intervention strategies for addressing disruption conditions). In fact, in the management of failures, to date, there are operational procedures which are based on hypothetical times for re-establishing ordinary conditions, estimated by the train driver or by the staff of the operation centre, who, generally, tend to minimise the impact exclusively from the company’s point of view (minimisation of operational costs), rather than from the standpoint of passengers. Additionally, in the definition of intervention strategies, passenger flow and its variation in time (different temporal intervals) and space (different points in the railway network) are rarely considered. It appears obvious, therefore, how the proposed re-examination of the dispatching and rescheduling tasks in a passenger-orientated perspective, should be accompanied by the development of estimation and forecasting techniques for travel demand, aimed at correctly taking into account the peculiarities of the railway system; as well as by the generation of ad-hoc tools designed to simulate the behaviour of passengers in the various phases of the trip (turnstile access, transfer from the turnstiles to the platform, waiting on platform, boarding and alighting process, etc.). The latest workstream in this present study concerns the analysis of the energy problems associated to rail transport. This is closely linked to what has so far been described. Indeed, in order to implement proper energy saving policies, it is, above all, necessary to obtain a reliable estimate of the involved operational times (recovery times, inversion times, buffer times, etc.). Moreover, as the adoption of eco-driving strategies generates an increase in passenger travel times, with everything that this involves, it is important to investigate the trade-off between energy efficiency and increase in user generalised costs. Within this framework, the present study aims at providing a DSS (Decision Support System) for all phases of planning and management of rail transport systems, from that of timetabling to dispatching and rescheduling, also considering space-time travel demand variability as well as the definition of suitable energy-saving policies, by adopting a passenger-orientated perspective

Risk-Based Optimal Scheduling for the Predictive Maintenance of Railway Infrastructure

In this thesis a risk-based decision support system to schedule the predictive maintenance activities, is proposed. The model deals with the maintenance planning of a railway infrastructure in which the due-dates are defined via failure risk analysis.The novelty of the approach consists of the risk concept introduction in railway maintenance scheduling, according to ISO 55000 guidelines, thus implying that the maintenance priorities are based on asset criticality, determined taking into account the relevant failure probability, related to asset degradation conditions, and the consequent damages

Cost Factor Focused Scheduling and Sequencing: A Neoteric Literature Review

The hastily emergent concern from researchers in the application of scheduling and sequencing has urged the necessity for analysis of the latest research growth to construct a new outline. This paper focuses on the literature on cost minimization as a primary aim in scheduling problems represented with less significance as a whole in the past literature reviews. The purpose of this paper is to have an intensive study to clarify the development of cost-based scheduling and sequencing (CSS) by reviewing the work published over several parameters for improving the understanding in this field. Various parameters, such as scheduling models, algorithms, industries, journals, publishers, publication year, authors, countries, constraints, objectives, uncertainties, computational time, and programming languages and optimization software packages are considered. In this research, the literature review of CSS is done for thirteen years (2010-2022). Although CSS research originated in manufacturing, it has been observed that CSS research publications also addressed case studies based on health, transportation, railway, airport, steel, textile, education, ship, petrochemical, inspection, and construction projects. A detailed evaluation of the literature is followed by significant information found in the study, literature analysis, gaps identification, constraints of work done, and opportunities in future research for the researchers and experts from the industries in CSS

A review of discrete-time optimization models for tactical production planning

This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

Evolutionary Algorithms in Engineering Design Optimization

Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any requisite to the objective/fitness evaluation function (continuity, derivability, convexity, etc.); they are not limited by the appearance of discrete and/or mixed variables or by the requirement of uncertainty quantification in the search. Moreover, they can deal with more than one objective function simultaneously through the use of evolutionary multi-objective optimization algorithms. This set of advantages, and the continuously increased computing capability of modern computers, has enhanced their application in research and industry. From the application point of view, in this Special Issue, all engineering fields are welcomed, such as aerospace and aeronautical, biomedical, civil, chemical and materials science, electronic and telecommunications, energy and electrical, manufacturing, logistics and transportation, mechanical, naval architecture, reliability, robotics, structural, etc. Within the EA field, the integration of innovative and improvement aspects in the algorithms for solving real world engineering design problems, in the abovementioned application fields, are welcomed and encouraged, such as the following: parallel EAs, surrogate modelling, hybridization with other optimization techniques, multi-objective and many-objective optimization, etc

Optimisation de la planification intégrée de la maintenance préventive et de la production des systèmes multi-états

Cette thèse traite la problématique de la planification intégrée de la maintenance préventive et de la production des systèmes multi-états. Il s'agit d'un système de production modélisé comme étant un système multi-états avec un nombre fini de niveaux de capacité allant du fonctionnement parfait jusqu'à la défaillance totale. Il doit produire un ensemble de produits pour satisfaire une demande donnée durant l'horizon de planification. Les composantes du système multi-états sont assujetties à des remplacements préventifs et à une réparation minimale en cas de panne. Ce travail présente des modèles de planification permettant de générer simultanément le plan optimal de production au niveau tactique (problème de taille de lot capaci-taire) et les instants ou les intervalles d'intervention pour des actions de maintenance préventive. Les fonctions des objectifs de ces modèles minimisent la somme des coûts de la maintenance (préventive et corrective) et des coûts de production sujets à des contraintes de satisfaction de demande et de capacité. La méthodologie proposée développe des modèles mathématiques, des méthodes d'évaluation des temps de maintenance, des coûts de maintenance, les capacités relatives aux systèmes et des algorithmes de résolution pour obtenir des solutions optimales (recherche exhaustive) ou approximatives (algorithmes génétiques et recuit simulé). Cette méthodologie a été utilisée dans les trois contributions suivantes : 1. La première contribution propose un modèle de planification de la maintenance préventive périodique et de la production pour un système multi-états. Il s'agit de déterminer le plan de production optimal et les longueurs des intervalles de remplacement pour chaque composante du système. 2. La deuxième contribution traite du problème de la planification intégrée de la maintenance préventive acyclique et de la production dans le cas d'une seule machine. Le plan optimal détermine le plan de production et les instants d'intervention pour des activités de maintenance préventive. 3. La troisième contribution propose un modèle une planification simultanée de la maintenance préventive acyclique et de la production pour un système multi-états composé de plusieurs composantes. Les résultats obtenus dans cette thèse montrent l'impact économique réalisé par l'intégration de la planification de la maintenance préventive et de la production, ainsi que pour l'élimination de la contrainte de périodicité, surtout dans le cas d'une demande fluctuante. Les méthodes de résolution développées dans ces travaux permettent la résolution de problèmes de petite ou de grande taille