Stochastic flow shop scheduling model for the Panama Canal

The Panama Canal can be modeled as a stochastic flexible flow shop for the purpose of scheduling. A metaheuristic stochastic optimization method (Nested Partition) was used to determine if current scheduling practices could be improved by reducing the makespan for vessel traffic. Results indicate that classifying the vessels according to the time that they spend transiting the canal and using some rules and metaheuristic technique for parallel flow shop improves the makespan. The schedules produced by this method show distinct patterns as described by the sequence of vessel types

The Relationship between Vehicle Routing & Scheduling and Green Logistics - A Literature Survey

The basic Vehicle Routing and Scheduling Problem (VRSP) is described followed by an outline of solution approaches. Different variations of the basic VRSP are examined that involve the consideration of additional constraints or other changes in the structure of the appropriate model. An introduction is provided to Green Logistics issues that are relevant to vehicle routing and scheduling including discussion of the environmental objectives that should be considered. Particular consideration is given to VRSP models that relate to environmental issues including the timedependent VRSP, the transportation of hazardous materials and dynamic VRSP models. Finally some conclusions are drawn about further research needs in this area and the relation to road pricing

The integrated control of production-inventory systems

In this thesis, we investigate a multi-product, multi-machine production-inventory (PI) system that is characterized by: ?? relatively high and stable demand; ?? uncertainty in the precise timing of demand; ?? variability in the production process; ?? job shop routings; ?? considerable setup times and costs. This type of PI system can be found in the supply chain of capital goods. Typically, it represents a manufacturer of parts that are assembled in later stages of the supply chain. Our exploratory research aims at identifying promising control approaches for this type of PI systems and the conditions in which they are applicable. The control approaches developed in this thesis are based on an integrated view of the PI system. The objective of the control approaches is to minimize the sum of setup costs, work-in-process holding costs and ¿nal inventory holding costs, while target customer service levels are satis¿ed. The research reveals that the exact analysis and optimization of this type of PI systems is impossible. Therefore, we are restricted to the development of heuristic control approaches. We propose two control strategies that are based on distinct control principles. For each of the control strategies, we develop and test decision-support systems that can be used to determine cost-e¢ cient (but not necessarily optimal) control decisions. Part I of this thesis deals with the ¿rst approach, called Coordinated Batch Control (CBC). This strategy uses a periodic review, order-up-to inventory pol- icy to control the stock points. The replenishment orders generated by this inventory policy are manufactured by the production system. The CBC strat- egy integrates production and inventory control decisions by determining cost- e¢ cient review periods. There is no further integration of control decisions. At the shop ¿oor, a myopic rule is used to sequence the orders, which ensures a certain degree of ¿exibility for responding to unexpected circumstances. We develop three decision-support systems for the CBC approach. The ¿rst decision-support system is based on an approximate analytical model of the PI system. In the approximate analytical model, we apply standard results from inventory theory, queueing theory and renewal theory. The second and third decision-support system use simulation optimization techniques to determine the near-optimal review periods. The three heuristic decision-support systems for CBC are tested in an exten- sive simulation study. The test bed consists of ¿ve basic problem con¿gurations, which de¿ne a routing structure, processing times, etc. We vary four factors over several levels: setup costs, setup times, net utilization and target ¿ll rates. In this way, we obtain 48 instances based on the same basic problem con¿guration, leading to 5 x 48 = 240 problem instances. The simulation study shows that the use of simulation optimization resulted in relatively small improvements over the solution obtained from the approximate analytical model. Since simulation optimization requires large amounts of computation e¤ort, we decide that the use of the decision-support system based on the approximate analytical model is justi¿ed. Part II is concerned with the Cyclical Production Planning (CPP) strategy. This strategy approaches the control of the PI system from a totally di¤erent angle. In this strategy, a detailed production schedule is used to control the production system. The schedule prescribes the sequence in which the orders are produced on the work centers and this schedule is repeated at regular time intervals. The time that elapses between the start of two schedules is called the ¿cycle time¿. The schedule is determined such that the total costs are minimized. The stock points are controlled with periodic review, order-up-to policies. The main advantage of the use of a production schedule is that ¿ow of the orders through the production system is controlled better, which results in more re- liable throughput times. A drawback of this approach is that the production frequencies of the di¤erent products need to be matched in order to make a cyclic production schedule. Hence, there is less ¿exibility in setting the lot sizes, which may result in higher costs. Another drawback of the CPP approach is that production capacity may be wasted by strictly following the prespeci¿ed processing sequences. We propose a decision-support system for the CPP strategy which is based on a deterministic model of the PI system. The decision-support system is used to determine cost-e¢ cient production plans. We present a heuristic method to approximately minimize the total costs of the deterministic model. When the solution of the deterministic model is used in a stochastic environment, the solution may be instable or nearly instable. Therefore, we use a simulation procedure to check whether the proposed solution is stable. If not, slack-time is added to the schedule and deterministic model is solved again. We test the decision-support system for CPP in an extensive simulation study. The test bed is identical to the one used in Part I. We test wether the Summary 273 decision-support system responds soundly to changes in the factors. Further- more, we investigate the estimation quality of the deterministic model that is embedded in the decision-support system. Finally, we test the optimization quality of the decision-support system. Based on the results of these tests, we decide that it is acceptable to use the proposed decision-support system to determine the control variables of the CPP strategy. Part III compares the performance of the CBC and the CPP strategy. Both strategies are compared in a simulation study consisting of the same instances as in Part I and II. We compare the strategies in terms of realized total costs. In about 62% of the instances, the CPP strategy outperforms the CBC strategy. In the remaining 38% of the instances, the CBC strategy realizes lower costs than the CPP strategy. An analysis of variance reveals that the following factors have a signi¿cant impact on the performance di¤erence between CPP and CBC: ?? net utilization; ?? setup costs; ?? interaction between setup costs and net utilization; ?? basic problem con¿guration. Based on our investigations, we can provide an explanation for these obser- vations. The simulation results show that the performance di¤erence is pro- portional to the di¤erence between the average review periods (CBC) and the common cycle length (CPP), denoted as dR. The factors mentioned above have an in¿uence on dR through their impact on capacity utilization. At low lev- els of capacity utilization, we observe that dR is low, which indicates that the CPP and CBC strategy operate with comparable review periods and common cycle lengths. In situations where the CBC strategy operates at higher levels of capacity utilization (because net utilization increases and/or setup costs de- crease), it becomes more di¢ cult for the CPP strategy to ¿nd a feasible cyclical production schedule, mainly because production capacity is wasted by strictly following a prespeci¿ed processing sequence. In these cases, the CPP strategy needs to increase the common cycle length to free up production capacity that is used to compensate for the loss of capacity. This leads to increases in dR and to higher costs. The speci¿c characteristics of a problem instance have a strong in¿uence on the magnitude of this e¤ect. Based on the insights obtained from our research, we formulate some guidelines for the application of CPP and CBC

Inventory routing problem with stochastic demand and lead time

In the supply chain, the integration of the different processes is critical to obtain high levels of coordination. Inventory control and its distribution are two of these processes whose coordination have been demonstrated by researchers as key in order to gain efficiency and effectiveness. They affect the synchronization of the supply chain management. With the intention to contribute to the integration of these processes and improve the problems of demand variability, we propose an integration of operations research area and the help of metaheuristics in a multi-objective approach. The expected results are to reduce the costs associated with inventory and its distribution, as well as to reduce the uncertainty in making decisions based on demand. This thesis presents methods for obtaining and analyzing near optimally solutions for dynamic and stochastic inventory-routing problems. The methods include retailers selection and clustering methods, algorithms and experiments on benchmark instances. We focus on problems with one and several suppliers that serve several dispersal geographically retailers. The thesis contains four parts. In Part I, we focus on the literature review. We first provide an overview of the literature on problems related to the coordination of the inventory and its distribution. Then we make a point in four elements: information management, inventory policies, stochastic demand and optimization methods. Also, we provide a scientometric analysis of the documentation collected in the last ten years. We provide a thorough review of papers working with dynamic and stochastic demand. The contributions of this part are i) the review of papers working with stochastic demand and stochastic lead times focusing on its stochastic and multi-depot aspects, ii) identify critical factors for the performance of many logistics activities and industries, iii) have shown that studying the behavior of the demand and the lead time are essential in order to achieve a useful representation of the system to take proper decisions and iv) provide the trends and patterns in the research in IRP problems. In Part II, we focus on the methodology of the research and of development. We first introduce the problem, state of the science, the gaps in the literature, variables under study, the instruments applied and assumptions. The development methodology is presented by a general model to address this type of research proposed in this thesis. Here, the general development process, decomposition of the problem and how the possible solutions are explained.. The importance of the this chapter is provided an effective way to face IRP problems. In Part III, the foundations in formulations for IRP problems are proposed. We begin with the formulation of the TSP problems with variants for one and many suppliers, likewise for VRP and IRP problems. The contributions of the model presented here aim identifying the variables and mathematical models frequently used to deal with these problems. In Part IV, we perform a single criteria objective and multi-criteria analysis of the solutions for one and many suppliers instances. Our methods yield significant improvements over a competing algorithm. Our contributions are i) propose three new customer selection methods for a dynamic and stochastic inventory-routing vii problem, ii) perform a multi-criteria analysis of the solutions, comparing distribution versus inventory management, iii) perform a single criteria objective experiment on benchmark instances from the literature.En la cadena de suministro, la integración de los diferentes procesos que la conforman, es fundamental para obtener altos niveles de coordinación. El control del inventario y su distribución son dos de estos procesos, cuya coordinación ha sido demostrada por los investigadores como clave para lograr mejoras en eficiencia y efectividad. Estos a su vez, afectan la sincronización y la administración de la cadena de suministro. Con el propósito de contribuir en la integración de éstos procesos y mejorar los problemas derivados de la variabilidad de la demanda, se propone usar los fundamentos del área de investigación de operaciones y la ayuda de metaheurísticas en un enfoque multi-obejtivo. Los resultados esperados son reducir los costos asociados a los procesos de inventario y distribución, así como también reducir la incertidumbre en la toma de decisiones a partir de la demanda. Ésta tesis presenta métodos para el análisis y obtención de soluciones cercanas a las óptimas para problemas de inventario y routeo, dinámico y estocástico. Los métodos incluyen selección de retailers y métodos de clustering, algoritmos y experimentos en instancias de prueba disponibles en la literatura. Se hace énfasis en instancias de un solo proveedor y varios proveedores que sirven varios retailers distribuidos geográficamente. La tesis está organizada en cuatro partes. En la Parte I, se revisa la literatura, para ello, primero se presentan los problemas relacionados con la coordinación del inventario y su distribución. Ésta revisión resalta cuatro elementos que han sido identificados como claves en la literatura como son: la administración de la información, políticas de inventario, demanda estocástica y métodos de optimización. Luego, se presenta un análisis cienciometrico de la literatura encontrada en los últimos 10 años. La revisión de la documentación se realiza de manera exhaustiva trabajando con demanda dinámica y estocástica. Las contribuciones de esta parte son: i) proporcionar una revisión pertinente y actualizada de artículos que emplean demanda estocástica, enfatizando en sus elementos dinámicos y estocásticos, así como también en aspectos que permitan abordar problemas con múltiples depósitos, ii) identificar factores críticos para el desempeño de actividades logísticas, iii) Demostrar que el estudio de la demanda es esencial para lograr una representación útil del sistema, la cual influye en la toma de decisiones y iv) proporcionar tendencias y patrones en la investigación de problemas de IRP. En la Parte II se aborda la metodología de la investigación y de desarrollo. Primero, se presenta el problema, el estado de la ciencia y los gaps encontrados en la literatura. Luego se identifican las variables de estudio, los instrumentos aplicados y los supuestos utilizados. La metodología de desarrollo es presentada por medio de un modelo general para abordar éste tipo de investigaciones que nosotros proponemos en ésta tesis. Esta metodología aborda aspectos como: el procedimiento general de desarrollo, la descomposición del problema y la forma en que se prueban las posibles soluciones. En la Parte III, se presentan los fundamentos en la formulación de IRP. Primero se formulan los problemas TSP con variantes para un solo depósito y también paramúltiples depósitos, igualmente se hace para VRP e IRP. La contribución de los modelos presentados son la identificación de las variables y los modelos matemáticos que frecuentemente son usados para tratar con éste tipo de problemas. En la Parte IV se presentan dos experimentos. El primero para el análisis de instancias con uno sólo depósito y en el segundo para analizar instancias con múltiples depósitos. Los métodos usados producen mejoras sobre resultados obtanidos con algoritmos similares. Las contribuciones de ésta parte son: i) proponer tres nuevos métodos para la selección de retailers para IRP dinámicos y estocásticos, ii) realizar análisis multi-criterio de las soluciones, comparando la distribución con la administración del inventario y iii) realizar análisis de un solo objetivo sobre instancias de pruebas proporcionada por la literatura existente

Scheduling Problems

Scheduling is defined as the process of assigning operations to resources over time to optimize a criterion. Problems with scheduling comprise both a set of resources and a set of a consumers. As such, managing scheduling problems involves managing the use of resources by several consumers. This book presents some new applications and trends related to task and data scheduling. In particular, chapters focus on data science, big data, high-performance computing, and Cloud computing environments. In addition, this book presents novel algorithms and literature reviews that will guide current and new researchers who work with load balancing, scheduling, and allocation problems