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In this master thesis, we investigate a ride-sharing problem within the Dutch Ministry of Defence, characterized by multiple heterogeneous vehicles and depots, strict time constraints, consideration of user preferences, limitations on vehicle capacity, and flexible roles of drivers and riders. With a fleet of thousands of pool vehicles spread across multiple pool locations, optimizing vehicle usage becomes crucial due to emissions concerns and limited vehicle availability. One possibility to achieve this is by introducing ride-sharing, wherein individuals are permitted to take a brief detour for the purpose of dropping off and picking up others. We propose a static simulated annealing algorithm to generate schedules that facilitate this ride-sharing and apply it in an iterated local search. Besides, we introduce the concept of decoupling vehicles from their original pool locations, resulting in the possibility of returning vehicles to different pool locations than their point of origin. The multi-objective function aims to minimize the number of non-served users, the ratio of the total distance travelled to that without ride-sharing, the number of non-empty vehicles, and the deviation from the desirable occupation of vehicles at pool locations. Comparing our algorithm to the current manual approach, we observe significant improvements: increased number of planned users and reduced mileage through ride-sharing, while utilizing fewer vehicles and maintaining minimal deviation from the desired vehicle occupation at pool locations. Furthermore, combining ride-sharing and vehicle decoupling results in superior solutions, outperforming either approach alone. Secondly, we show the successful incorporation of single rides, which are rides from one pool location to another pool location without a return, and show that these increase the degree of ride-sharing. Lastly, our work presents a robustness analysis which demonstrates that rides can be effectively added to the genera

Defatted larvae meal (dLM), specifically from black soldier flies, could help overcome the animal protein gap. As insect production is an emerging sector, current economic research is scarce and very diverse. Thus, the aim of this research was to develop a simulation model that enables the analysis of full industrial scale costs of producing dLM and to provide insight in the distribution of these costs in the insect supply chain. The deterministic supply chain model is built on three modules, technical, transition and economic module, which all follow a previously defined supply chain structure and allow to extract quantity and price information for intermediate or final products. The model was parameterized and checked for plausibility in multiple consultation rounds with the INSECTFEED consortium and business partners. Additionally, model behaviour was checked with scenario, sensitivity, and breakeven price analyses. In the default situation 5.57 tDM raw substrate and 26.7 million neonates are required to produce 1 tDM dLM for a price of e5,116/tDM. Most costs are added in the raw substrate delivery (e1,952/tDM) and production and collection (e821/tDM) step. Important cost factors are the raw substrate (e1,939/tDM) and building and inventory (e1,459/tDM). Parameters with high relative response rate towards the price of dLM are the feed conversion rate, dry matter percentage of larvae, raw substrate price, larvae density, labour wage and growth rate. To reach break-even prices for substituting fish meal with alive grown larvae (AGL) (e1,318/tDM AGL), improving production parameters is not sufficient. Just changing prices of raw substrate to −e78/tDM or frass to e1,175/tDM would enable a profitable operation. However, these are not deemed as realistic in mass production. Although there is some insecurity in data, the model results are the most realistic representation of industrial scale production amounts and costs.

Since the abolishment of the milk quota system in Europe in 2014 and the introduction of environmental policies such as the phosphate rights system in the Netherlands, the reasons for culling dairy cows might have changed. The aim of this study was to determine the culling reasons for dairy cattle and to identify farmers' culling strategies and their intentions regarding the alteration of indicated culling strategies. To this end, an online questionnaire was distributed among dairy farmers nationally that resulted in 207 responses. Results showed that the most frequent culling reasons were related to problems with reproduction, udder, and hoof health. Primiparous cows were primarily culled for miscellaneous reasons such as injury, reproduction failure, and low milk yield. Multiparous cows were culled predominantly for reproduction failure, udder health and hoof health reasons. Most respondents indicated that they consider formulating a culling strategy, based on certain rules of thumb regarding the most common reasons for culling. Most farmers also reported that culling decisions on their farms were perceived to be unavoidable, though reproductive culling decisions are primarily voluntary. Most respondents stated that they intended to reduce the culling rate for better economic gain did not intend to alter the amount of replacement stock reared. The applied rules of thumb regarding culling strategies do not seem to have changed since the policy changes in dairy farming. The question remains whether farmers' rules of thumb might have made them unaware of the actual economic consequences of their culling strategies under the altered situation.

This randomized controlled trial on 4 commercial grazing dairy farms investigated whether pegbovigrastim (PEG) treatment affected partial net return as calculated from milk revenues and costs for feed, medical treatments [clinical mastitis, uterine disease, and other diseases (i.e., any medical treatment that was not intended for clinical mastitis or uterine disease)], inseminations, and culling during a full lactation in grazing dairy cows. We also explored the effect of potential interactions of PEG treatment with parity, prepartum body condition score, and prepartum nonesterified fatty acids concentration on partial net return, milk revenues, and the costs mentioned above. Holstein cows were randomly assigned to 1 of the 2 following trial arms: a first PEG dose 9.4 ± 0.3 (mean ± standard error) days before the calving date and a second dose within 24 hours after calving (PEG: primiparous = 342; multiparous = 697) compared with untreated controls (control: primiparous = 391; multiparous = 723). The effect of PEG treatment on the outcomes of interest expressed per year was tested using general linear mixed models. Results are presented as least squares means ± standard error. Overall, PEG treatment increased the partial net return, resulting in an economic benefit per cow per year of $210 ± 100. The cost of treatment of clinical mastitis was lower for PEG treated cows compared with control cows ($9 ± 3). The largest nonsignificant difference was seen for the cost of culling; additionally, PEG treatment numerically reduced the cost of culling by $145 ± 77.

Moderate to severe forms of suboptimal mobility on dairy cows are associated with yield losses, whereas mild forms of suboptimal mobility are associated with elevated somatic cell count and an increased risk to be culled. Although the economic consequences of severe forms of suboptimal mobility (also referred as clinical lameness) have been studied extensively, the mild forms are generally ignored. Therefore, the aim of the current study was to determine the economic consequences associated with varying prevalence and forms of suboptimal mobility within spring calving, pasture-based dairy herds. A new submodel predicting mobility scores was developed and integrated within an existing pastured-based herd dynamic model. Using a daily timestep, this model simulates claw disorders, and the consequent mobility score of individual cows. The impact of a cow having varying forms of suboptimal mobility on production and reproduction was simulated. The economic impact was simulated including treatment costs, as well as the production and reproductive impacts of varying levels of suboptimal mobility. Furthermore, different genetic predispositions for mobility issues and their interaction with herd-level management associated with each level of suboptimal mobility were simulated. Overall, 13 scenarios were simulated, representing a typical spring calving, pasture-based dairy herd with 100 cows. The first scenario represents a perfect herd wherein 100% of the cows had mobility score 0 (optimal mobility) throughout the lactation. The remaining 12 scenarios represent a combination of (1) 3 different herd-management levels, and (2) 4 different levels of a genetic predisposition for suboptimal mobility. The analysis showed that a 17% decrease in farm net profit was achieved in the worst outcome (wherein just 5% of the herd had optimal mobility) compared with the perfect herd. This was due to reduced milk yield, increased culling, and increased treatment costs for mobility issues com