This research investigates ways to maximize the outbound handling and freight to customer operations efficiency based on the real data of The Kraft Heinz Company. A cost to serve model has been developed to evaluate the performance of various design alternatives deriving from the field of "quantity adjustment" as the dependence of cost efficiency upon labour intensity at the warehouses and the truck volume utilization indicated. The research concludes upon the selection of the optimal design alternative to be implemented per customer as well as upon which design alternative is more suitable for clusters of customers that share specific characteristics.

Since the commercialisation of air travel, demand for air transport is increasing. Optimal system capacity utilisation at airports has therefore become crucial. As available resources such as land, buildings and human are scarce and airline tickets need to be financially affordable, airports optimise their system while maximising capacity within the constraints of safety and reliability. Regional airports, that often provide remote stands which are not connected to the terminal building, need to obey to and cope with an incremental number of operational planning rules in order to provide safe and secure apron operations. Current operational apron planning procedures imply a remote stand allocation that results in a corresponding gate assignment and a passenger apron transfer including a mode choice between pedestrian and bus transport. This study will add to research by fundamentally changing this approach into an integrated optimisation procedure. This entails simultaneously optimising the remote stand allocation, gate assignment and apron passenger transfer by means of an integrated mixed integer linear programming model. The model objective is to minimise the total apron transfer duration and therefore apron utilisation time. Experiments on a Rotterdam The Hague Airport case study show that the integrated optimisation procedure provides the potential of an average apron passenger time saving of 18% given the optimised stand-gate-route allocations. As a result of remaining model limitations, this research leaves the opportunity for the integration of apron aircraft movements to include the impact of jet blast. Furthermore, the potential of a rolling horizon approach could be researched to include system uncertainty over time and the potential to update the operational planning.

In the competitive offshore wind installation market, contractors like DEME strive to optimize operations. This thesis centers on the optimization of the support vessel fleet composition, which consist of a num- ber of walk to work vessels, and are a crucial part of inter-array cable installation. By fine-tuning this composition, operational expenses can be reduced by 10-20% to current industry practices. The cable installation process involves a complex set of operations, each necessitating a crew to be present on the foundations. Support vessels play a central role in routing of these crews and their equip- ment to these foundations.This thesis introduces an innovative approach that integrates operational scheduling and crew routing into a single formulation for optimizing the fleet of walk-to-work vessels. This hybrid model combines elements of a continuous-time rich multi-visit multi-period Vehicle Routing Problem with a time-varying Resource Constrained Project Scheduling Problem. It also factors in the substantial impact of weather conditions on offshore operations by accounting for variable weather win- dows in each scheduling period. The formulated model is rigorously verified and validated to ensure it closely mirrors real-world sup- port vessel behavior. Although it slightly underestimates fuel consumption, this discrepancy is deemed acceptable given its minor role in the overall objective. Sensitivity analyses highlight the critical impor- tance of accurate performance data for the cable laying vessel, which significantly influences the model’s outcomes. However, the model is found to be most effective for modeling a single cable string compris- ing 6-8 turbines, with scalability issues arising when attempting to expand beyond this scope. A focused case study delves into the impact of various weather conditions and inter-array distances on the optimal vessel composition. The study evaluates two types of walk-to-work vessels, individually and in combination. Results reveal that, under the assumption of zero downtime, the industry norm of chartering cheaper vessels is cost-effective, while the pricier vessel results in a 10% costlier solu- tion. As weather conditions worsen, a composition of costlier vessels proves more cost-effective over the scheduling horizon. Such conditions are to be expected in far offshore locations, especially on the cheaper vessels, which have lower workability limits. The study identifies potential cost reductions of up to 25%, with even marginal downtime conditions yielding 10-20% reductions to the industry standard. Moreover, delays imposed on the cable laying vessel are significantly reduced when utilizing a compo- sition that includes at least as one of the more expensive vessels. In summary, this thesis establishes a foundation for optimizing support vessels in offshore wind installa- tion. The presented model introduces a novel framework, combining multi-visit routing with time-varying resource scheduling, while considering shared vehicles and coupled routing and scheduling over a multi- period horizon. For regions prone to harsh weather conditions, such as those further offshore and during winter months, it is advised to utilize more expensive vessels that have higher workability limits and bet- ter performance figures. Additionally, there appears to be limited justification for simultaneous use of multiple vessels during the cable installation, as the added costs do not seem to outweigh the marginal improvements in installation duration. Future research should focus on refining solution methods for the proposed formulation and incorporating crew transfer vessels into the fleet composition.

Jumbo Maritime is a company specialized in handling and transporting substantial cargoes which did not fit into a container. To compete in the heavy lift shipping market, a well-balanced fleet composition is essential. In the current situation, the heavy lift cargoes are transported by a fleet consisting of ten vessels, having a varying crane lifting capacity from 3000*10^3 to 650 *10^3 kilogram (Class K, H, J and E). However, in the past five years, it has become apparent that the deployment of the vessels based on the heaviest item (between 75-100% of the capacity) has only been needed in a meagre five percent of all transportations. The installed crane capacity on the Jumbo vessels are an overcapacity compared to the demand of the market. During this research, a decision support tool is developed to improve the match between the demand from the market in the heavy lift cargo industry and the supply of the heavy lift shipping vessels. This will result in an improved fleet composition that maximizes profit. Subsequently, the tool has been examined to see whether it can henceforth be applied to the fleet composition to support Jumbo Maritime in its leading role of supplying heavy loads.The Maritime Fleet Size & Mix Problem model was used to find the optimal fleet composition. The goal of this model is to maximize profit, achieved from transport orders based on reduced cost of the vessels. Considering that the proceeds of a load depend on market demand, the transport data of the past five years has been used as an input parameter. A fleet is chosen by taking into consideration both the technical and financial aspects. The technical aspect is the maximum combined crane capacity installed on the vessels. The financial aspects of the vessels exist of capital costs, labour costs, fuel costs and maintenance costs. The result of this model will lead to an optimization in the distribution of the vessel.Subsequently, the vessels that are at the end of their life will be replaced in the near future. The Vessels classified under H and E will be replaced by a variety of the newer J-light classes. The decision about the composition of the new vessels in the Jumbo fleet should be supported by the optimization model. The new vessels will be used as input in the model, together with the prediction data of possible future market needs. These future predictions will consist of three scenarios: 1) the demand will stay the same as it has been for the past five years; 2) Demands will rise with 6% due to an increase in the oil and gas industry; 3) a 35% increase in the renewable energy related market. The result of the three scenarios will be a new fleet composition with a corresponding profit.An optimal fleet composition will be the result when the transport data of the past five years, together with the current fleet characteristics, are used as input for the Maritime Fleet Size & Mix Problem. The current fleet composition [2:4:2:2] is in the optimized situation as followed [1:2:1:8], whereby the theoretical gain increases from 108 million to 181 million. When the future scenarios one, two and three together with the new vessel types (K: J: J-900: J-800: J-700: J-600) are introduced, new optimum fleet compositions arise. The new optimized compositions are as follows: scenario one: [1:1:0:1:0:6] with a profit of 56 million, scenario two: [1:1:0:1:0:6] with a profit of 68 million and scenario three [1:1:0:1:0:6] with a profit of 58 million.The results of the Maritime Fleet Size & Mix Problem show that the profit can be optimized with an alternative fleet composition. The mathematical model determines the composition of the fleet by using the transport data from the past five years. The optimization model is subjected to a number of assumptions to approach the reality. By also using the Maritime Fleet Size & Mix Problem model with the introduction of the J-light and combining it with the three different future scenarios, the vessel type with a combined crane capacity of 600 tonnes appears to be the most efficient in the J-light class.

This thesis contributes to the research of a complementary Truck Arrival Management system in order to increase the efficiency of the Liquid Bulk Terminal as a system in a global intermodal supply chain. Nowadays, terminals often suffer from congestion, despite the use of a Truck Arrival Management system. A Truck Arrival Management system controls truck arrivals at terminals. Currently, the Truck Appointment System is the most used and researched Truck Arrival Management system at terminals. The Truck Appointment System has advantages and disadvantages. Therefore, Drop and Swap has been researched as second Truck Arrival Management system. A complementary Truck Arrival Management system is developed and researched in which Truck Appointment System and Drop and Swap cooperate with the objective to overcome disadvantages and enhance benefits. The system should be capable to serve all kind of trucks within the global intermodal supply chain.

The order picking process is done item by item, and therefore it is a labour-intensive process. According to Dukic & Oluic (2005), 50% of the total order picking time is spent on unproductive traveling. The operations that need to be performed in warehouses are highly dependent on the customer demand. The customer demand shows seasonal patterns spread over the year caused by so-called seasonal influences. The objective of this research was to investigate and identify the opportunities and possibilities regarding the order picking process to react to the seasonal impact that influences the productivity of order picking. Order picking can be described as a warehouse process of retrieving products from storage in response to specific customer request and bringing them to an area dedicated for collecting the assembled customer orders. Order picking can be performed in a variety of Order Picking Systems (OPS). This study focusses on the lower automatization level of pick-and-sort batch picking using a picker-to-parts system. An insight of demand profiles in certain time series and order characteristics have been obtained by using a decomposition model with multiplicative seasonal-adjustment. Patterns in number of orders, items/order, weight/item and volume/item were determined for setting up design alternatives. The alternatives are based on some primary interdependent policies proposed in the study of Wascher (2004): storage policy, routing policy, zoning policy, and order consolidation policy. The three design alternatives in this study are: class-based randomized storage, volume-based randomized storage, and zone decomposition. These alternatives are tested in a model with discrete event simulation for both regular and peak periods, compared to a base alternative. The KPIs are cycle picking time and the variable order picking (labour) costs and both need to be minimized. All three design alternatives seem to be promising for future order picking operations compared to the base alternative. The results of this study show that major savings can be reached changing the order picking strategy in general. For companies, focusing on the reduction of travel distance of the operators can lead to more efficient processes in the fulfilment centre and in the end cause a decrease in labour costs. However, it is recommended for the company of the case study, to implement the class-based randomized storing policy. On yearly basis, the order picking costs decrease with 12%. Looking at cycle time and travel distances, even higher savings can be obtained in future operation by deploying the zone decomposition dynamically during peak periods. This means that during peak periods, zones are dynamically divided into two sub-zones causing a decrease in travel distance between picks, leading to lower cycle picking times.

As the margins for improvements in the current freight transport system become limited, researchers address more and more the importance of collaboration between the actors which is crucial for the implementation of new, more efficient transport concepts as synchromodality. In addition, rail is concerned as a sustainable mode of transport that can also achieve economies of scale due to its ability to haul large quantities of goods. This study investigates cooperation policies that affect actors’ behavior to better utilize the rail use and lead to a more efficient system. We propose an innovative approach that combines gaming, simulation and optimization as a mixed method to test and evaluate these policies. The port to hinterland freight transportation system in the range of Port of Rotterdam is used as a case study. First, gaming sessions are organized in order to observe actors’ behavior and collect data. The game that is used was initiated by Port of Rotterdam, especially to identify the problems in this system. Subsequently, by assessing the observed data, a simulation model is developed and different policy scenarios are simulated to quantify their performance. In addition, the optimization model is developed, which sets the upper bound for performance and used as a solid base for comparison between the policy alternatives. Finally, the explanation of the difference between the policies’ and the optimized performance can give an insight on what are the root causes of the inefficiency, what is the best allocation of the resources and where the solutions should be focused.

Aircraft component maintenance, repair, and overhaul (MRO) outsourcing is a rather new phenomenon. Nowadays, component support solutions that are flexible with predictable cost are pursued. In other words, the time to restore and cost of MRO are aimed to be minimised. This research project is collaboration with one of the worlds leaders in aircraft MRO: KLM Engineering & Maintenance. Notable is the unbalanced allocation of jobs to shops due to obsolete contractual agreements, whereas the flexibility to deviate slightly from these agreements is available. Several task to shop assignment policies are developed and evaluated using discrete event simulation. The policies are an extension of the classic assignment problem and are aspired to reduce either the time to restore a component, the cost of MRO, and seek for a solution that includes both attributes. The result of the deployed experimental design is a non-dominating set of solutions where the trade-off between cost and time is clearly recognised. A policy where both cost and time are considered, with emphasis on time, results in a reduction of both performance indicators. However, other policies perform considerably better in terms of either cost or time. The established Pareto front provides a proper basis for further optimisation and depicts the choices for the MRO provider clearly.

With an increase in amount of container terminals competition between terminals has risen. Therefore it has become more and more important for terminal operators to conduct their work as efficient as possible. Efficient terminal operations are hindered by stochasticity, which is defined as random variation in parameter values. Due to missing information on exact arrival times, requested containers are often stored underneath other containers, which will then need to be reshuffled to reach the requested container. This reshuffling is performed while a hinterland transport mode is waiting for the requested container and therefore increases service times and SC utilisation during peak hours. This research investigates the relation between stochasticity and terminal stacking performance of import containers with a simulation model. Terminal stacking performance is subdivided into the Key Performance Indicators reshuffles per retrieval, truck service time and maximum straddle carrier utilisation per hour. The results show that implementing housekeeping moves can spare the entire import yard up to 639 764 reshuffles per year, 8 854 hours in truck serving per year and 8 minute per peak hour per SC. Even in the experiments where the level of stochasticity is high, a saving of 120 656 reshuffles per year, 883 hours truck service time and 3 minutes per SC peak hour are observed. The higher the level of stochasticity, the smaller the improvement on the KPIs is. Lastly, it can be concluded that stacking performance also deteriorates when the level of stochasticity becomes higher.

Efficient distribution is crucial in many industries today, especially in retail, where customer demand grows rapidly. The rise of online shopping and automation has led to a shift towards using Central Distribution Centers (CDCs). Retailers are part of this trend, which requires them to rethink how they handle their distribution. This study focuses on two main challenges: first, changing the distribution system to adapt to new CDCs, and second, dealing with the computational complexities when optimizing the distribution on a large scale. The aim is to design a large distribution system for the allocation of stores and the routing of vehicles. In this research, we introduce new elements to the mathematical model, which are mostly focused on the routing of vehicles. We also improve the computation by implementing a start solution, adjusting the parameters of the Gurobi optimization tool and including a callback function which bounds the run time. This model will determine the routing decisions for demand from several DCs to the stores and find the optimal vehicle routes. Through a case study at a company in the Netherlands, this paper provides insights into the changing world of distribution systems. It offers practical solutions for businesses trying to make their distribution processes better. The analysis revealed that consolidating demand at CDCs can lead to significant cost improvements while altering transport costs between CDCs and RDCs and adjusting order volumes can influence delivery strategies. Despite the absence of direct relationships between routing decisions, distances, and volumes, a logistic regression model provides guidance.

This research focuses on identifying and evaluating ways to improve the sustainability of solid waste management (SWM) in semi-public spaces using the Efteling theme park as a case study. To the best of the author’s knowledge, this study is the first to apply an integrated waste management approach to optimize SWM in this context. The approach consists of assessing the integrated environmental and economic burdens of the collection, transportation, sorting and treatment processes of a SWMstrategy. Approximately 10 alternative high potential SWM strategies were composed and selected out of a very large pool of possible SWM strategies. The environmental and economic impact of these high potential SWM strategies for the Efteling case was subsequently assessed using the WARM LCA model and a custom economic assessment model. The results reveal that emission reductions of up to 190 ton CO2 equivalents (TCO2E’s) per year, relative to the current strategy, can already be achieved by separating and recycling more fractions from behind-the-scenes (BTS) waste. This corresponds to an increase in yearly avoided SWM system emissions of about 25% for the Efteling case (from a life-cycle perspective). When public/semi-public (PSP) waste is also included, emission reductions of up to 800 TCO2E’s per year can be achieved for single-fraction separation (e.g. PMD or PET) and up to 960 TCO2E’s per year for two-fraction separation (e.g. PMD + paper or PMD + cups). This corresponds to major increases in avoided SWM system emissions of 110% and 131% respectively. It was also found that small interventions in the transport and/or treatment waste management components can make a big difference in the environmental and/or economic impact of a SWM strategy. A majority of the alternative SWM strategies has an eco-efficiency (emission reduction cost-effectiveness) ranging from €39 to about €140 per TCO2E saving. This eco-efficiency is (much) higher than that of a range of benchmarks such as the eco-efficiency of solar-pv panels at a non-industrial scale, wind turbines at sea and the eco-efficiency of office building insulation. This indicates that optimizing waste management should be given more priority in (scientific) research as well as in practice.

In this report, supply chains of factory outlet stores are analyzed. Here, the concept of factory outlet stores have been investigated in literature to be able to understand which goal these stores serves. Based on a pull based supply chain perspective, replenishment has been investigated. Here, demand forecast, inventory, order ful_llment and transport have been considered. Here, transport models from literature are introduced to see which factors are considered and for which purpose these models can be used. Also, the performance of supply chain has been discussed, which consists of _nancial as non _nancial aspects. A case study will be done at the factory outlet store of L'Oreal. Here, the supply chain has been analyzed, as the catalogue and type of products they o_er. The replenishment policy has been analyzed, in which the transport process from the CPD warehouse to the store will be investigated. Here, a model will be designed to be able to schedule the deliveries to the store in a more cost e_cient way. An analytical modelling method is selected to develop a model which captures the mentioned transport process. Here, aspects of models in literature are evaluated to be used in the transport model for scheduling deliveries. The model is developed as an integer mixed linear programming model and will schedule the amount of pallets per delivery to a storage location, in which two storage location are presented. This model is described as the delivery scheduling transport model (DSTM) and is checked on implementation in MATLAB in a veri_cation step. The DSTM has been con_gured for the case study at L'Oreal, which is checked by a validation step to see if the model meets the system requirements. Then, experiments with di_erent inputs are executed to see if savings can be realized by scheduling the transport via this model. This is realized in all the inputs scenarios. To see if more savings can be realized, sensitivity analysis have been performed to investigate how parameters can be tuned to realize lower cost. A conclusion will _nalize this research to conclude that replenishment orders can be scheduled in a more cost e_cient way by the DSTM, which is the result of a case study of L'Oreal.

With the increasing need for more sustainable transportation, the electrification of IWW shipping becomes of great relevance. There are several ways to achieve this, from which the implementation of an exchangeable battery system is discussed in this research. Several challenges arise from the large-scale implementation of such a system. One of which is the optimal distribution of the batteries and the location of the docking stations to guarantee electric sailing for a certain demand of vessels. By developing a time-discrete mixed-integer linear programming optimisation model the outputs of this research aim at assessing this. The obtained results showed the optimisation opportunities and possible synergies that can be achieved when vessels share the batteries and charging infrastructure. Though, it is not trivial to determine beforehand the optimal result for different inputs, through different scenario analysis, information that can be useful to assist the strategic decision of the system implementation from a logistic perspective can be obtained.

This research focused on the techno-economic implementation of Sustainable Aviation Fuels (SAF). Carbon reduction in commercial aviation could be done via four key levers; technological efficiency improvement (aircraft or engine replacement), operational efficiency improvement (air traffic management or airline operations), the implementation of Sustainable Aviation Fuels, and carbon offsetting by using economic measures. This research was done by doing a case study at TUI Aviation, thus using their demand data. After developing a traffic forecast and resulting CO2 forecast, the four levers were used to limit carbon emissions toward a net-zero emission scenario in 2050. The 22 ASTM certified SAF alternatives were tested against carbon mitigation power and costs, the latter being determined by using the experience curve theory of decreased prices with increased cumulative production. This results in the FT-SPK fuel made from Municipal Solid Waste as being the most attractive SAF alternative with a Net Present Value of 875 million USD. However, it is recommended to include extra fuel alternatives in this research in the future. For example, Power-to-Liquid fuels will have great potential, but are not certified yet.

The use of petroleum-based fuels in the shipping sector creates harmful emissions that need to be reduced to reach climate goals. Ammonia is being considered as a possible fuel to reduce emissions, but there exist several challenges that prevent its implementation. Research into these several of these challenges is being done, but there is little research into the bunkering process of ammonia. Therefore, the purpose of this research is to identify an installation to bunker ammonia that is suitable for ports that handle sea-going vessels. In order to do this, requirements, functions and alternatives are proposed for this system. Subsequently, these alternatives are evaluated through an ordinal analysis and a decision is made on a configuration through the Best Worst Method (BWM). To do this, Stakeholders from the port of Rotterdam are surveyed and used as input for the BWM. A viable configuration is found that adheres to all requirements. Finally, it is concluded that the configuration is applicable to multiple ports due to the general prioritization of safety, robustness of the result and similar results between stakeholders with different secondary priorities. Furthermore, the effectiveness of mitigation strategies implies sufficiently small risk contours, to allow ports that are in close proximity to vulnerable objects to be able to build an ammonia bunker installation as well.

To convey the energy coming from offshore wind-farms to the end-users, a network of offshore transmission platforms with sub-sea cables is in place, functioning as the supply chain for electricity. This research addresses the development of an optimization model, OptiFleet, which targets the problem of vessel fleet management to perform the transportation of crew and cargo to and from the platforms. OptiFleet provides strategic decision support to the Transmission System Operator on the optimal accommodation and transportation strategy. In particular the model aims to generate an optimum fleet size and mix, this is the number and the type of vessels in the fleet to support the platform maintenance campaigns.

High-speed rail (HSR) is frequently seen as a promising alternative for long-distance travel by air and road, given its environmental advantages whilst offering a competitive level of service. However, due to a lack of knowledge on the design of HSR specific line configurations and the prioritisation of national and railway company interests, no real European HSR network has been realised yet. Together, these lead to a sub-optimal performance from a user, operator and societal perspective. This research is the first attempt to apply the more frequently used ‘Transit Network Design and Frequency Setting Problem’ (TNDFSP) in an HSR setting, which searches the ideal set of lines and associated frequencies in a given network. To do so, this study developed a novel HSR generic model and solution algorithm, which were then parameterised for the European case. By benchmarking the current situation; analysing the relative importance of vehicle, passenger path and line design variables; evaluating pricing and governance strategies; and finally proposing improved settings; it was possible to assess the impacts of improved design. The experiments showed that benefits for all stakeholders could be simultaneously enhanced when implementing a centralised governance and internalisation of external costs. This allowed the HSR market share to evolve from 14.7% to 29.9%, whilst also improving the societal cost-benefit ratio by 20.0%. The governmental investment which is required to fill the gap from the most economical to the most extensive solution equals AC 2.2 billion per year, but also provides a positive rate of return of 1.8 for the combined user and societal benefits. Additionally, the model demonstrated the necessity of spilling unprofitable passengers and the importance of improved cooperation. These followed from the strong network integration with overlapping and border crossing lines of substantial lengths, the contradiction between national and international interests and the high number of critical infrastructural elements. All in all, this study demonstrated the possibility of using the TNDFSP in an HSR setting, which opens ways for further understanding of HSR network design. For this specific research, it allowed the identification of substantial opportunities for mobility and sustainability. These can be reached by improved design choices, internalisation of external costs and by relaxation of the desires for a competitive railway market and national sovereignty; all newly underpinned arguments for the discussion on how to design a successful (European) HSR system. Future research could greatly contribute by incorporating the construction of infrastructure, including timetabling or operational aspects, assessing different case studies in size and geography or introducing new technologies.

A promising vision to make the global logistics more sustainable is 'Physical Internet Logistics'. This vision, based on the way 'Digital Internet' sends packages information through a network, is focused on optimisation of handling, storing, realising and supplying objects. Physical Internet Logistics suggests an open, global and interconnected network with different spokes, hubs and modes. Objects are encapsulated in standardised containers whereafter they will be distributed through a network. Routing of the container is focused on network balancing. Every container will follow its own path through the network from origin to destination by using different hubs. Different origin-destination pairs will be bundled and transported on the same link. Besides, similar origin-destination pairs could follow different paths through the network. At hubs, transhipment takes place to transfer containers to different routes. This paper is focused on the application of Physical Internet characteristics in the parcel delivery industry using an optimisation model concerning fleet allocation on a service network. The objective is to find such a fleet allocation plan in which the total amount of emitted CO2 is minimised. Two different designs are suggested: a 'hub design' and an 'open network design'. For the hub network design, a couple of nodes are defined as hub where transhipment can take place. Paths from origin to destination are only possible by using at least one hub. This means that demand travels from origin to hub to destination. For the Open network design, transhipment is possible at every node. Paths from origin to destination are possible in one direct way or by using a hub. This means that two kinds of paths are possible, from origin to destination or from origin to hub to destination. By using a case study at PostNL, a carrier in the Dutch parcel delivery industry, this paper concludes that the application of Physical Internet characteristics do have its influence. In particular, the openness of a network result in a reduction in total amount of emitted CO2. During the case study at PostNL, it became clear that a CO2 reduction of 6% is possible when the elements of Physical Internet were applied on a hub network design. The open network design is able to reduce the total amount of emitted CO2 by 16%. When the demand is known by forehand this paper concludes that a less restricted network results in less CO2 emissions emitted. Destinations should be severed by more than one hub or directly by the origin depot. Transhipment should be possible at as much as nodes as possible. Concerning a case in the parcel delivery industry, it is hard to make forecasting more reliable on a daily base due to the short time windows of delivery. This means that a carrier as PostNL should innovate in the flow of information from shippers to make the application of Physical Internet feasible.

Industrial railway systems can be found within companies where the production and processing of goods require large quantities to be transported. These underdeveloped systems are often privately owned and are characterized by short to cover distances, many locations, inefficient layout due to historical expansion and bidirectional driving. Local optimization in such a system does not directly lead to a global improvement. This research suggest a new model to define and measure the performance of the system as a whole by using customer value from the theory of lean thinking combined with prioritization of transport tasks. In order to test the model and to optimize the capacity of an industrial railway system a case study is performed at the railway system of Tata Steel IJmuiden, the Netherlands. Through implementing the new customer value model into a discrete event simulation, a set of improvements in the field of locomotive assignment strategy, work schedule, network configuration and fleet size resulted in a global 10.7 percent improvement in performance.

This thesis investigates different ways in which the productivity of a one-way bottling and packaging production line can be increased. This is done by comparing different configurations regarding machine capacities, machine reliability and buffer capacities with each other. This is done with both the use of a generic model and a case study. The different configurations were compared and combined together with the use of a simulation model. Following from this it can be concluded that it is dependent on the reliability and the machine capacities which shape of protective capacity is the most productive. Besides, also the place in the system where the largest amount of buffer capacity needs to be placed is dependent on the reliability of the machines which are part of the production line.