On the integration of diverging material flows into resource‐constrained project scheduling

This study deals with an extension of the resource-constrained project scheduling problem (RCPSP) by constraints on material flows released during the execution of project activities. These constraints arise from limited processing capacities for materials and maximum inventories of intermediate storage facilities. Production scheduling problems with converging material flows have been studied extensively. However, this is the first project scheduling problem integrating diverging material flows typically observed in dismantling projects, e.g., building deconstruction, power plant decommissioning, or battery/car decommissioning. Diverging material flows do not directly impact the project planning but only impose delays in the case of congestion. We model material flows by using operations that represent the processing of materials, and cumulative resources that represent storage facilities. As a method for efficiently generating starting solutions, we propose a schedule generation scheme tailored to the particular precedence structure of such problems. Furthermore, we extensively study the schedule generation scheme’s performance on generated test instances and compare it to the constraint programming solver IBM ILOG CP Optimizer. It turns out that the solution quality strongly depends on the employed model and that neither of the two solution methods is generally superior

A graph based process model measurement framework using scheduling theory

Software development processes, as a means of ensuring software quality and productivity, have been widely accepted within the software development community; software process modeling, on the other hand, continues to be a subject of interest in the research community. Even with organizations that have achieved higher SEI maturity levels, processes are by and large described in documents and reinforced as guidelines or laws governing software development activities. The lack of industry-wide adaptation of software process modeling as part of development activities can be attributed to two major reasons: lack of forecast power in the (software) process modeling and lack of integration mechanism for the described process to seamlessly interact with daily development activities. This dissertation describes a research through which a framework has been established where processes can be manipulated, measured, and dynamically modified by interacting with project management techniques and activities in an integrated process modeling environment, thus closing the gap between process modeling and software development. In this research, processes are described using directed graphs, similar to the techniques with CPM. This way, the graphs can be manipulated visually while the properties of the graphs-can be used to check their validity. The partial ordering and the precedence relationship of the tasks in the graphs are similar to the one studied in other researches [Delcambre94] [Mills96]. Measurements of the effectiveness of the processes are added in this research. These measurements provide bases for the judgment when manipulating the graphs to produce or modify a process. Software development can be considered as activities related to three sets: a set of tasks (τ), a set of resources (ρ), and a set of constraints (y). The process, P, is then a function of all the sets interacting with each other: P = {τ, ρ, y). The interactions of these sets can be described in terms of different machine models using scheduling theory. While trying to produce an optimal solution satisfying a set of prescribed conditions using the analytical method would lead to a practically non-feasible formulation, many heuristic algorithms in scheduling theory combined with manual manipulation of the tasks can help to produce a reasonable good process, the effectiveness of which is reflected through a set of measurement criteria, in particular, the make-span, the float, and the bottlenecks. Through an integrated process modeling environment, these measurements can be obtained in real time, thus providing a feedback loop during the process execution. This feedback loop is essential for risk management and control

Makespan Minimization in Re-entrant Permutation Flow Shops

Re-entrant permutation flow shop problems occur in practical applications such as wafer manufacturing, paint shops, mold and die processes and textile industry. A re-entrant material flow means that the production jobs need to visit at least one working station multiple times. A comprehensive review gives an overview of the literature on re-entrant scheduling. The influence of missing operations received just little attention so far and splitting the jobs into sublots was not examined in re-entrant permutation flow shops before. The computational complexity of makespan minimization in re-entrant permutation flow shop problems requires heuristic solution approaches for large problem sizes. The problem provides promising structural properties for the application of a variable neighborhood search because of the repeated processing of jobs on several machines. Furthermore the different characteristics of lot streaming and their impact on the makespan of a schedule are examined in this thesis and the heuristic solution methods are adjusted to manage the problem’s extension

Unrelated parallel machine scheduling problem: a cement industry case study

Dissertação de mestrado em Engenharia de SistemasThis dissertation considers the problem of scheduling unrelated parallel machines, with unequal release dates and machine eligibility constraints, to minimize the total flow time of the system. It establishes an analogy between this problem and an existing process in the cement industry { the loading of trucks by the customers. Hence, it intends to find opportunities for improvement in the reduction of the customers' interaction times and in their experience inside the cement plants. To achieve this goal, three optimization models are proposed, one exact and two heuristics. Also, an extensive series of computational tests are carried out to compare the performance of the methods. The exact method, based on a mathematical formulation of the problem, requires a high computational time and it is incapable of dealing with large instances. Consequently, it is not a viable solution for an industrial sized problem. However, it contributes to a better understanding of the structure of the problem and to develop efficient heuristics. The heuristics, one based on dispatching rules and the other on a simulated annealing algorithm, show potential for the implementation in a real life scenario. Although simulated annealing gives considerably better solutions than the other heuristic, it takes more time to give results and it is more complex to implement. The dispatching rules based heuristic gives solutions almost instantly and more easily includes certain characteristics of the problem. In general, these methods improve the quality of service provided, reducing the overall time the customers are spending inside the cement plants. Thus, cement industry can and should use optimization models to improve their operations and the customers' experience.Esta dissertação considera o problema de agendamento de máquinas paralelas não relacionadas, com datas de disponibilidades diferentes e restrições de elegibilidade, para minimizar o tempo total de fluxo do sistema. Esta estabelece também uma analogia entre este problema e um processo existente na indústria cimenteira - o carregamento de camiões pelos clientes. Assim, pretende encontrar oportunidades de melhoria na redução dos tempos de interação dos clientes e na sua experiência dentro das cimenteiras. Para atingir este objetivo, três modelos de otimização são propostos, um exato e duas heurísticas. Além disso, uma extensa série de testes computacionais é realizada para comparar o desempenho dos métodos. O método exato, baseado numa formulação matemática do problema, requer bastante tempo computacional e é incapaz de lidar com instâncias grandes. Consequentemente, não é uma solução viável para um problema de tamanho industrial. No entanto, contribui para uma melhor compreensão da estrutura do problema e para desenvolver heurísticas eficientes. As heurísticas, uma baseada em regras de despacho e a outra num algoritmo de simulated annealing, mostram potencial para uma implementação num cenário da vida real. Embora o simulated annealing ofereça soluções consideravelmente melhores do que a outra heurística, este necessita de mais tempo para fornecer resultados e é mais complexo de implementar. A heurística baseada em regras de despacho fornece soluções quase instantaneamente e pode incluir mais facilmente certas características do problema. Em geral, estes métodos melhoram a qualidade do serviço prestado, reduzindo o tempo total que os clientes gastam dentro das cimenteiras. Assim, a indústria cimenteira pode e deve usar modelos de otimização, para melhorar as suas operações e a experiência dos clientes