Operational Control of Internal Transport

Operational Control of Internal Transport considers the control of guided vehicles in vehicle-based internal transport systems found in facilities such as warehouses, production plants, distribution centers and transshipment terminals. The author's interest of research having direct use for practice has resulted in a combination of theoretical and practical research in vehicle-based internal transport systems. An overview is given of the related literature and results are presented that show how different vehicle dispatching rules behave in different environments

Intelligent Control of Vehicle-Based Internal Transport Systems

“Intelligent control of vehicle-based internal transport (VBIT) systems” copes with real-time dispatching and scheduling of internal-transport vehicles, such as forklifts and guided vehicles. VBIT systems can be found in warehouses, distribution centers, manufacturing plants, airport and transshipment terminals. Using simulation of two realworld environments, dispatching rules described in literature and several newly introduced rules are compared on performance. The performance evaluation suggests that in environments where queue space is not a restriction, distance-based dispatching rules such as shortest-travel-distance-first outperform time-based dispatching rules such as modified-first-come-first-served and using load prearrival information has a significant positive impact on reducing the average load waiting time. Experimental results also reveal that multi-attribute dispatching rules combining distance and time aspects of vehicles and loads are robust to variations in working conditions. In addition, multi-attribute rules which take vehicle empty travel distance and vehicle requirement at a station into account perform very well in heavy-traffic VBIT systems such as baggage handling systems. Besides dispatching rules, the potential contribution of dynamic vehicle scheduling for VBIT systems is investigated. Experiments using simulation in combination with optimization show that when sufficient pre-arrival information is available a dynamic scheduling approach outperforms the dispatching approach. This thesis also evaluates the impact of guide-path layout, load arrival rate and variance, and the amount of load pre-arrival information on different vehicle control approaches (scheduling and dispatching). Based on experimental results, recommendations for selecting appropriate vehicle control approaches for specific situations are presented

Efficient yard storage in transshipment container hub ports

Ph.DDOCTOR OF PHILOSOPH

Optimal Planning of Container Terminal Operations

Due to globalization and international trade, moving goods using a mixture of transportation modes has become a norm; today, large vessels transport 95% of the international cargos. In the first part of this thesis, the emphasis is on the sea-land intermodal transport. The availability of different modes of transportation (rail/road/direct) in sea-land intermodal transport and container flows (import, export, transhipment) through the terminal are considered simultaneously within a given planning time horizon. We have also formulated this problem as an Integer Programming (IP) model and the objective is to minimise storage cost, loading and transportation cost from/to the customers. To further understand the computational complexity and performance of the model, we have randomly generated a large number of test instances for extensive experimentation of the algorithm. Since, CPLEX was unable to find the optimal solution for the large test problems; a heuristic algorithm has been devised based on the original IP model to find near „optimal‟ solutions with a relative error of less than 4%. Furthermore, we developed and implemented Lagrangian Relaxation (LR) of the IP formulation of the original problem. The bounds derived from LR were improved using sub-gradient optimisation and computational results are presented. In the second part of the thesis, we consider the combined problems of container assignment and yard crane (YC) deployment within the container terminal. A new IP formulation has been developed using a unified approach with the view to determining optimal container flows and YC requirements within a given planning time horizon. We designed a Branch and Cut (B&C) algorithm to solve the problem to optimality which was computationally evaluated. A novel heuristic approach based on the IP formulation was developed and implemented in C++. Detailed computational results are reported for both the exact and heuristic algorithms using a large number of randomly generated test problems. A practical application of the proposed model in the context of a real case-study is also presented. Finally, a simulation model of container terminal operations based on discrete-event simulation has been developed and implemented with the view of validating the above optimisation model and using it as a test bed for evaluating different operational scenarios

Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals

Tesis por compendioDespite the continuous evolution in computers and information technology, real-world combinatorial optimization problems are NP-problems, in particular in the domain of planning and scheduling. Thus, although exact techniques from the Operations Research (OR) field, such as Linear Programming, could be applied to solve optimization problems, they are difficult to apply in real-world scenarios since they usually require too much computational time, i.e: an optimized solution is required at an affordable computational time. Furthermore, decision makers often face different and typically opposing goals, then resulting multi-objective optimization problems. Therefore, approximate techniques from the Artificial Intelligence (AI) field are commonly used to solve the real world problems. The AI techniques provide richer and more flexible representations of real-world (Gomes 2000), and they are widely used to solve these type of problems. AI heuristic techniques do not guarantee the optimal solution, but they provide near-optimal solutions in a reasonable time. These techniques are divided into two broad classes of algorithms: constructive and local search methods (Aarts and Lenstra 2003). They can guide their search processes by means of heuristics or metaheuristics depending on how they escape from local optima (Blum and Roli 2003). Regarding multi-objective optimization problems, the use of AI techniques becomes paramount due to their complexity (Coello Coello 2006). Nowadays, the point of view for planning and scheduling tasks has changed. Due to the fact that real world is uncertain, imprecise and non-deterministic, there might be unknown information, breakdowns, incidences or changes, which become the initial plans or schedules invalid. Thus, there is a new trend to cope these aspects in the optimization techniques, and to seek robust solutions (schedules) (Lambrechts, Demeulemeester, and Herroelen 2008). In this way, these optimization problems become harder since a new objective function (robustness measure) must be taken into account during the solution search. Therefore, the robustness concept is being studied and a general robustness measure has been developed for any scheduling problem (such as Job Shop Problem, Open Shop Problem, Railway Scheduling or Vehicle Routing Problem). To this end, in this thesis, some techniques have been developed to improve the search of optimized and robust solutions in planning and scheduling problems. These techniques offer assistance to decision makers to help in planning and scheduling tasks, determine the consequences of changes, provide support in the resolution of incidents, provide alternative plans, etc. As a case study to evaluate the behaviour of the techniques developed, this thesis focuses on problems related to container terminals. Container terminals generally serve as a transshipment zone between ships and land vehicles (trains or trucks). In (Henesey 2006a), it is shown how this transshipment market has grown rapidly. Container terminals are open systems with three distinguishable areas: the berth area, the storage yard, and the terminal receipt and delivery gate area. Each one presents different planning and scheduling problems to be optimized (Stahlbock and Voß 2008). For example, berth allocation, quay crane assignment, stowage planning, and quay crane scheduling must be managed in the berthing area; the container stacking problem, yard crane scheduling, and horizontal transport operations must be carried out in the yard area; and the hinterland operations must be solved in the landside area. Furthermore, dynamism is also present in container terminals. The tasks of the container terminals take place in an environment susceptible of breakdowns or incidences. For instance, a Quay Crane engine stopped working and needs to be revised, delaying this task one or two hours. Thereby, the robustness concept can be included in the scheduling techniques to take into consideration some incidences and return a set of robust schedules. In this thesis, we have developed a new domain-dependent planner to obtain more effi- cient solutions in the generic problem of reshuffles of containers. Planning heuristics and optimization criteria developed have been evaluated on realistic problems and they are applicable to the general problem of reshuffling in blocks world scenarios. Additionally, we have developed a scheduling model, using constructive metaheuristic techniques on a complex problem that combines sequences of scenarios with different types of resources (Berth Allocation, Quay Crane Assignment, and Container Stacking problems). These problems are usually solved separately and their integration allows more optimized solutions. Moreover, in order to address the impact and changes that arise in dynamic real-world environments, a robustness model has been developed for scheduling tasks. This model has been applied to metaheuristic schemes, which are based on genetic algorithms. The extension of such schemes, incorporating the robustness model developed, allows us to evaluate and obtain more robust solutions. This approach, combined with the classical optimality criterion in scheduling problems, allows us to obtain, in an efficient in way, optimized solution able to withstand a greater degree of incidents that occur in dynamic scenarios. Thus, a proactive approach is applied to the problem that arises with the presence of incidences and changes that occur in typical scheduling problems of a dynamic real world.Rodríguez Molins, M. (2015). Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48545TESISCompendi

Horizontale en verticale samenwerking in distributieketens met cross-docks

Logistiek dienstverleners staan voor grote uitdagingen op het gebied van duurzaamheid, in het bijzonder vanwege de steeds kleiner wordende zendingen die just-in-time bij de klant moeten worden afgeleverd. Samenwerking tussen partners in de distributieketen en met concurrenten daarbuiten biedt kansen om deze uitdagingen het hoofd te bieden. Dit proefschrift richt zich op samenwerkingsvormen in distributieketens met cross-docks. Cross-docks zijn logistieke centra die bedrijven in staat stellen om kleine zendingen gegroepeerd te transporteren zonder dat daarvoor tussentijdse opslag nodig is. In een cross-dock worden goederen direct van inkomende naar uitgaande vrachtwagens verplaatst. Het succesvol toepassen van cross-docking vereist verticale samenwerking tussen partners in opeenvolgende stadia van de distributieketen. Horizontale samenwerking ontstaat tussen mogelijk concurrerende bedrijven die vergelijkbare activiteiten in verschillende distributieketens uitvoeren. Dit proefschrift presenteert theoretische modellen voor horizontale en verticale samenwerking in distributieketens met cross-docks en bestudeert oplossingsmethodieken waarmee de duurzaamheid van deze ketens kan worden verbeterd. Daarvoor worden concepten uit de vakgebieden informatiesystemen, Operations Research en Supply Chain Management gecombineerd. De in dit proefschrift beschreven classificatie van wiskundige cross-docking modellen onthult nieuwe onderzoeksvragen gericht op een betere afstemming tussen interne cross-dock processen en ketenlogistiek. Een simulatiestudie illustreert hoe geringe aanpassingen in de ketenlogistiek tot grote prestatieverbeteringen in het cross-dock leiden. Op het gebied van horizontale samenwerking is een methode ontwikkeld die de uitwisseling van ladingen tussen transporteurs systematiseerd. Een reeks casussen toont aan dat doorbraken in ICT ontwikkeling nodig zijn om samenwerkende transporteurs in staat te stellen gezamenlijk planningsbeslissingen te nemen

Development of a simulation model of a Company X shunting yard

Thesis (M.Com. (Marketing Management and Information Systems))--University of the Witwatersrand, Faculty of Commerce, Law and Management, School of Economic and Business Sciences, 2016.It was realised that there are inefficiencies at Company X’s plant K shunting yard; service time was long and the idling time of the locomotives was long. Locomotives can be utilised for other purposes in the plant. This has implication in resource planning and productivity in the company. The study deals with the simulation of the Company X rail network in plant K. The focus is on how shunting and product transportation takes place. A background on the study is given, taking into consideration elements which have been included in the study. These include the locomotives and the Block Train Rail Tanker Cars (RTCs). These containers transport different products from Town L to Town M. The study focuses on the transportation of five products. The study also includes the domestic and international Product E trains arriving at the Product E loading and offloading zone. Simulation model which represents the current-state situation was developed, using SIMIO software package. The study examined how service speed during the process of loading and offloading of products in the plant can be improved. The study also focused on locomotives travelling speed and idling time. Conclusions and recommendations have been made on the model developed. The results obtained were also discussed and analysed.DH201