Browsing by Subject "Optimization"

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Application of nature-inspired optimization algorithms to improve the production efficiency of small and medium-sized bakeries
(2023) Babor, Md Majharul Islam; Hitzmann, Bernd
Increasing production efficiency through schedule optimization is one of the most influential topics in operations research that contributes to decision-making process. It is the concept of allocating tasks among available resources within the constraints of any manufacturing facility in order to minimize costs. It is carried out by a model that resembles real-world task distribution with variables and relevant constraints in order to complete a planned production. In addition to a model, an optimizer is required to assist in evaluating and improving the task allocation procedure in order to maximize overall production efficiency. The entire procedure is usually carried out on a computer, where these two distinct segments combine to form a solution framework for production planning and support decision-making in various manufacturing industries. Small and medium-sized bakeries lack access to cutting-edge tools, and most of their production schedules are based on personal experience. This makes a significant difference in production costs when compared to the large bakeries, as evidenced by their market dominance. In this study, a hybrid no-wait flow shop model is proposed to produce a production schedule based on actual data, featuring the constraints of the production environment in small and medium-sized bakeries. Several single-objective and multi-objective nature-inspired optimization algorithms were implemented to find efficient production schedules. While makespan is the most widely used quality criterion of production efficiency because it dominates production costs, high oven idle time in bakeries also wastes energy. Combining these quality criteria allows for additional cost reduction due to energy savings as well as shorter production time. Therefore, to obtain the efficient production plan, makespan and oven idle time were included in the objectives of optimization. To find the optimal production planning for an existing production line, particle swarm optimization, simulated annealing, and the Nawaz-Enscore-Ham algorithms were used. The weighting factor method was used to combine two objectives into a single objective. The classical optimization algorithms were found to be good enough at finding optimal schedules in a reasonable amount of time, reducing makespan by 29 % and oven idle time by 8 % of one of the analyzed production datasets. Nonetheless, the algorithms convergence was found to be poor, with a lower probability of obtaining the best or nearly the best result. In contrast, a modified particle swarm optimization (MPSO) proposed in this study demonstrated significant improvement in convergence with a higher probability of obtaining better results. To obtain trade-offs between two objectives, state-of-the-art multi-objective optimization algorithms, non-dominated sorting genetic algorithm (NSGA-II), strength Pareto evolutionary algorithm, generalized differential evolution, improved multi-objective particle swarm optimization (OMOPSO) and speed-constrained multi-objective particle swarm optimization (SMPSO) were implemented. Optimization algorithms provided efficient production planning with up to a 12 % reduction in makespan and a 26 % reduction in oven idle time based on data from different production days. The performance comparison revealed a significant difference between these multi-objective optimization algorithms, with NSGA-II performing best and OMOPSO and SMPSO performing worst. Proofing is a key processing stage that contributes to the quality of the final product by developing flavor and fluffiness texture in bread. However, the duration of proofing is uncertain due to the complex interaction of multiple parameters: yeast condition, temperature in the proofing chamber, and chemical composition of flour. Due to the uncertainty of proofing time, a production plan optimized with the shortest makespan can be significantly inefficient. The computational results show that the schedules with the shortest and nearly shortest makespan have a significant (up to 18 %) increase in makespan due to proofing time deviation from expected duration. In this thesis, a method for developing resilient production planning that takes into account uncertain proofing time is proposed, so that even if the deviation in proofing time is extreme, the fluctuation in makespan is minimal. The experimental results with a production dataset revealed a proactive production plan, with only 5 minutes longer than the shortest makespan, but only 21 min fluctuating in makespan due to varying the proofing time from -10 % to +10 % of actual proofing time. This study proposed a common framework for small and medium-sized bakeries to improve their production efficiency in three steps: collecting production data, simulating production planning with the hybrid no-wait flow shop model, and running the optimization algorithm. The study suggests to use MPSO for solving single objective optimization problem and NSGA-II for multi-objective optimization problem. Based on real bakery production data, the results revealed that existing plans were significantly inefficient and could be optimized in a reasonable computational time using a robust optimization algorithm. Implementing such a framework in small and medium-sized bakery manufacturing operations could help to achieve an efficient and resilient production system.
Characterization of the effects of chia gels on wheat doughand bread rheology as well as the optimization of breadroll production with the Nelder-Mead simplex method
(2016) Zettel, Viktoria; Hitzmann, Bernd
Chia (Salvia hispanica L.) is becoming increasingly popular as ingredient for baked goods. The aim of the first part of this thesis was to investigate the influence of gel from ground chia on the rheology of different wheat dough systems and the resulting baked goods. The evaluated products were wheat bread and sweet pan bread. The effects of chia incorporated as gel in wheat bread dough as hydrocolloid were characterized using empirical and fundamental rheological methods and differential scanning calorimetry. To avoid competition of starch and ground chia with respect to the water uptake, chia was incorporated as gel. The gel was prepared of ground chia with 5 g/g and 10 g/g water, respectively. The doughs were prepared with 1-3 % chia related to the amount of wheat flour. The effects of gel from ground chia were studied also as fat replacer in sweet pan breads. The main focus of the work was to study the effects of the fat substitution on the dough rheology. The dough rheology was characterized using a rotational rheometer and a Rheofermentometer. The end products were evaluated with a texture analyser and two samples were additionally evaluated with respect to their fatty acid profile. The substitution was secondly addressed to reduce the total amount of fat in the product and to improve the nutritional value of the products regarding the fatty acid composition. The fat was replaced in four steps, and the ratio among the ingredients was held constant to ensure a better comparability. Within this thesis it was shown that addition of gel from ground chia can affect wheat doughs and the resulting baked products in a positive way. The approach of using ground chia as gel seems to be fruitful to avoid competition between starch and chia with respect to the water uptake while the crumb formation during the baking process takes place. The evaluation of the pasting profiles of wheat flour suspensions with chia gel addition reinforced this assumption. The gel from ground chia affected the pasting properties in a way that the viscosities decreased with increasing amount of chia. The rheological properties of the doughs were affected in negative ways with respect to further processing by the addition of too high amounts of chia gel. The dough stability was reduced and the resulting baked products were less and irregular porous and therefore compact. All doughs showed weakening regarding the rheometer measurements, however the linear viscoelastic region was not affected. The frequency sweep measurements showed for all doughs a decrease with increasing content of gel from ground chia. The creep-recovery tests of the sweet pan bread doughs revealed that the zero viscosity η0 decreased and the creep compliance J0 increased with increasing chia gel content. The weakening of the doughs may not absolutely be caused by the incorporated chia, but by the additional water. There seems to be a kind of interaction between ground chia particles, wheat flour constituents and water, because nearly the same results were achieved for 2 % and 1 % of ground chia with 5 g/g and 10 g/g water, respectively. These experiments lead also to the best results for incorporating gel from ground chia to wheat breads. The best results for sweet pan breads were obtained with 25 % fat replacement through gel from ground chia. This gel was prepared of 2.3 g ground chia with 5 g/g water. Summarizing the incorporation of defined amounts of gel from ground chia has a positive effect on the rheology and the resulting baked products. The retrogradation of the baked products was decreased over storage and the dietary fibre content was increased. Thus chia acts like a hydrocolloid. The nutritional values of the evaluated baked products, wheat bread and sweet pan bread, were increased. For the sweet pan breads an increase of omega-3 fatty acids was determined. The resulting best sweet pan bread exhibited an amount of 5 % linolenic acid. Gel from ground chia can therefore be incorporated into bakery products as hydrocolloid and for improving the nutritional values regarding the dietary fibre and omega-3 fatty acid contents. Another part of the work was the optimization of the production parameters, proofing time and baking temperature, for bread rolls. The optimization was performed with the Nelder-Mead simplex method. The optimization was necessary for a new oven type, where the oven walls were coated with a ceramic, that increased the infrared radiation during the baking process. The quality criterion for the optimization were the specific volume, the baking loss, the colour saturation, crumb firmness as well as the elasticity of the bread rolls. Within 11 experiments the optimal baking result defined by the results of a conventional oven was obtained. The optimal processing parameters for the bread rolls were a proofing time at 117 minutes and a baking temperature of 215 °C for 16 minutes.
Foam mat drying of cassava and associated properties : comparison between white-flesh and yellow-flesh varieties
(2021) Ayetigbo, Oluwatoyin Elijah; Müller, Joachim
Cassava is an important staple food crop in Africa, Asia and Americas, serving as food, raw material, feed, and source of livelihoods. However, cassava has poor post-harvest physiological stability, deteriorates rapidly, has high toxic cyanogenic contents and poor physicochemical properties. Foam mat drying was considered as a technique to combat these challenges. First, a comparison of the different properties of variants of cassava based on colour was made from the perspective of sustainability. Afterwards, an optimization of the foaming process was conducted for two varieties (white-fleshed and yellow-fleshed) of cassava using various foaming variables. Optimal variables were not different between both varieties. Foaming reduced cyanogenic toxicity and retained carotenoids in cassava significantly, but also had significant influence on colour. The foams developed had asymmetrical distribution in air bubble diameter, while foam powder microstructure showed close association between the hydrocolloids and starch. Furthermore, an optimization of the drying conditions of optimal cassava foams was conducted based on temperature and foam thickness. Drying kinetics (moisture removal ratio, diffusivity, dying rate) of the cassava foams and the effect of various drying conditions on selected physicochemical properties of cassava foam powder was researched. Two falling rates were found during drying, Diffusivity was significantly affected by temperature but not foam thickness. The cassava foam powders had acceptably low cyanogenic contents, and had high retention of carotenoids. Foam powder microstructure did not change significantly with temperature, but yellow cassava foam powder had higher coalescence.
Investigation of fluidised bed coating : measurement, optimisation and statistical modelling of coating layers
(2017) van Kampen, Andreas; Kohlus, Reinhard
Fluidised bed coating describes a process to encapsulate particles. The coating layer is applied in order to protect the core material from chemical reactions with the environment, to control the release of drugs or to mask bad taste. Depending on the application, the coating layer must fulfil various quality requirements, such as completeness, homogeneity and minimum layer thickness. The measurement of the coating layer thickness is therefore necessary in order to determine appropriate parameters for an optimal coating process. This, however, is difficult in the investigated core particle size range of 100 to 500 μm with a coating layer thickness of around 10 μm. Fluorescent imaging of sliced particles or imaging of optical slices using confocal laser scanning microscopy are possible ways to make the coating layer visible and to measure the coating layer thickness using image analysis techniques. This leads to detailed images of the coating layer and an accurate description of the coating layer thickness distribution, but is rather time consuming due to tedious sample preparation and long image acquisition times. Consequently only relatively few particles are measured and used to draw conclusions on the population. Other methods like measurement of the change of particle size using laser diffraction or assessment of the volume ratio of coating to core material usually only deliver the mean thickness and no information on completeness and homogeneity of the coating. In the first part of this thesis a quick method for coating thickness measurement was developed based on a dissolution test. Sodium chloride was used as a core material and maltodextrin DE21 was used as a coating material. When dissolved in deionised water, sodium chloride raises the conductivity in contrast to maltodextrin. Therefore, the measurement of conductivity can be used to assess the dissolution curve of the core material. The coating layer delays the dissolution of the core and by comparison with the dissolution curve of pure sodium chloride the coating thickness distribution can be assessed by deconvolution. It was shown that this method is well reproducible and delivers reliable results comparable to other methods. The method is fast, which enables the measurement of many samples with replicates and using appropriate sample division should provide a good representation of the population. The shape of the thickness distribution allows the quantification of the three aforementioned quality parameters. The method was therefore used in the second part of this thesis in order to investigate the coating process using design of experiments. The four factors spray rate, air temperature, air velocity and concentration of the coating solution were investigated using a central composite design of experiments. The dissolution method was used to assess the coating quality. The particle size distribution was measured in order to quantify the agglomeration rate and the mass of deposited coating material was assessed by quantifying a tracer colour in order to assess the efficiency of the process. Significant quadratic models were fitted to all response variables. These were successfully used to find a local optimum within the investigated parameter space which allowed the formation of an optimal coating layer within a short time frame. The results of the previous investigations showed that the thickness distribution can be well described by a Weibull distribution. Furthermore, it was possible to confirm effects that were previously described in the literature, i.e. that a low concentration of the coating solution leads to more homogeneous coating layers. In order to give a general description of the coating layer, a statistical model of the coating thickness distribution was developed in the third part of this thesis and verified by a Monte-Carlo simulation. The model reproduces the experimentally determined effect of the concentration of the coating solution qualitatively and is able to calculate the mean thickness distribution with given concentration, contact angle, sprayed mass and core particle and droplet size. Appropriate adjustments of these parameters lead to a good agreement between the model and measured thickness distributions of real experiments. It was concluded that predominant spray drying of small droplets and an increase of concentration of the remaining droplets due to pre drying negatively affects the homogeneity of the coating layer. It was further confirmed that the Weibull distribution can be used to describe the coating layer thickness in the investigated thickness range. The thickness distribution transitions from the Weibull distribution to a normal distribution as the coating becomes thicker. Thin coatings with defects can be described by a clinched Weibull distribution containing the uncoated area fraction as an offset.
Modelle und Lösungsverfahren zur langfristigen Planung der Stromproduktion einer flexiblen Biogasanlage unter Berücksichtigung von Verschleiß
(2021) Butemann, Hendrik; Schimmelpfeng, Katja
One of the most important measures against climate change is the shift from fossil to renewable energies. Many countries have therefore made it their goal to increase the share of renewable energies for electricity generation. In Germany, the share in 2019 was 40.2%, of which biomass accounted for 20.6%. This category includes biogas plants, which, unlike other sources of renewable energy, have the advantage of not being dependent on certain weather conditions. They are considered a flexible option for electricity generation because they can produce electricity when neither the sun is shining nor the wind is blowing. When the first biogas plants were put into operation, revenues from electricity production could be maximized by having the combined heat and power unit (CHP) associated with the biogas plant generate electricity continuously. To take advantage of the flexibility of biogas plants, German legislators introduced premiums that contained incentives to produce electricity during periods of low supply from other renewable energy sources. Since then, biogas plant operators have been able to maximize their revenues when the CHP produces electricity on demand, i.e., in start-stop mode. However, a large number of starts and stops of the CHP causes altered wear and tear and must be taken into account in the long-term planning of the electricity production of a biogas plant. The aim of this dissertation is therefore to use operations research methods to develop cyclical electricity production plans for biogas plants that take into account the wear and tear of the CHP and the timing and costs of maintenance activities in order to support biogas plant operators in maximizing their revenues. For this purpose, first a classification of electricity production planning of biogas plants into the planning tasks along the biomass-based supply chain is given. Subsequently, the basics of biogas plants are explained, which include their relevance in Germany, their way of operation, service and maintenance as well as the legal framework for their operation. The research gap, which is filled by this dissertation, results from the literature review on quantitative approaches for the operation of biogas plants. It shows that there is still no research work that sufficiently addresses the wear and tear of CHP in flexible operation and the planning of maintenance activities in connection with electricity production. Therefore, a conceptual optimization model is developed that accurately replicates the non-linear wear that occurs in reality and thus enables simultaneous planning of electricity production and maintenance activities. For better applicability with standard solvers, the model is additionally linearized. A case study based on real-world data reveals that a flexible biogas plant achieves higher total revenues than a continuously operated biogas plant under the conditions prevailing in Germany, even when maintenance costs are taken into account. The conceptual optimization model is then extended to produce a cyclical plan that biogas plant operators can apply on a weekly basis. In the following chapter, a greedy heuristic for generating a starting solution as well as a genetic algorithm and a tabu search are developed with the goal of reducing the computation time when solving the extended model. For this purpose, the basics of the individual solution methods are first explained and the input data are adapted to the problem with the help of parameter tuning. An extensive numerical study, in which the input parameters electricity prices, costs for maintenance activities, wear and tear of the CHP and biogas storage capacity are varied, compares the performance of the methods with that of the extended optimization model. In all scenarios, the tabu search determines the best result in low runtime. A summary and an outlook on further research opportunities conclude the dissertation.
Optimization of no-wait flowshop scheduling problem in bakery production with modified PSO, NEH and SA
(2021) Babor, Majharulislam; Senge, Julia; Rosell, Cristina M.; Rodrigo, Dolores; Hitzmann, Bernd
In bakery production, to perform a processing task there might be multiple alternative machines that have the same functionalities. Finding an efficient production schedule is challenging due to the significant nondeterministic polynomial time (NP)-hardness of the problem when the number of products, processing tasks, and alternative machines are higher. In addition, many tasks are performed manually as small and medium-size bakeries are not fully automated. Therefore, along with machines, the integration of employees in production planning is essential. This paper presents a hybrid no-wait flowshop scheduling model (NWFSSM) comprising the constraints of common practice in bakeries. The schedule of an existing production line is simulated to examine the model and is optimized by performing particle swarm optimization (PSO), modified particle swarm optimization (MPSO), simulated annealing (SA), and Nawaz-Enscore-Ham (NEH) algorithms. The computational results reveal that the performance of PSO is significantly influenced by the weight distribution of exploration and exploitation in a run time. Due to the modification to the acceleration parameter, MPSO outperforms PSO, SA, and NEH in respect to effectively finding an optimized schedule. The best solution to the real case problem obtained by MPSO shows a reduction of the total idle time (TIDT) of the machines by 12% and makespan by 30%. The result of the optimized schedule indicates that for small- and medium-sized bakery industries, the application of the hybrid NWFSSM along with nature-inspired optimization algorithms can be a powerful tool to make the production system efficient.
Optimizing the development of seed-parent lines in hybrid rye breeding
(2001) Tomerius, Alexandra-Maria; Geiger, Hartwig H.
In hybrid rye breeding, seed-parent and pollinator lines are developed from two divergent gene pools. Line development comprises selection for line performance per se followed by selection for combining ability to the opposite gene pool. Cytoplasmic-genic male sterility (CMS) is employed as hybridizing mechanism. This study deals with model calculations aiming to optimize and compare alternative schemes of seed-parent line development in hybrid rye breeding on the basis of their expected selection gain per year in an index comprising the most important breeding objectives. Prediction of selection gains rests on current estimates of quantitative-genetic and economic parameters. The schemes are optimized for the number of candidates, testers to assess testcross performance, test locations, and replicates at the individual selection stages. Optimization is carried out assuming a fixed annual budget. Five schemes are investigated which differ in the basic genetic material assumed, in the type of test units and the number of selection stages for line and testcross selection, and in the length. The standard scheme employs second cycle material. First, S2-lines are evaluated per se. Selection for combining ability is then carried out at two stages employing testcross progenies of the CMS analogues of the candidate lines in backcross generations BC1 resp. BC2. The first alternative scheme employs an additional stage of BC1L-testcross selection. Another scheme is suited for developing seed-parent lines from broader-based population material. In addition to these 'conventional' methods, a scheme using doubled haploid lines is investigated as well as a scheme in which testcross progenies are produced by means of a gametocide instead of CMS. The optimum dimensioning and relative efficiency of the schemes is investigated for various genetical and economical situations.
Optimum schemes for hybrid maize breeding with doubled haploids
(2011) Wegenast, Thilo; Melchinger, Albrecht E.
In hybrid maize breeding, the doubled haploid technique is increasingly replacing conventional recurrent selfing for the development of new lines. In addition, novel statistical methods have become available as a result of enhanced computing facilities. This has opened up many avenues to develop more efficient breeding schemes and selection strategies for maximizing progress from selection. The overall aim of the present study was to compare the selection progress by employing different breeding schemes and selection strategies. Two breeding schemes were considered, each involving selection in two stages: (i) developing DH lines from S0 plants and evaluating their testcrosses in stage one and testcrosses of the promising DH lines in stage two (DHTC) and (ii) early testing for testcross performance of S1 families before production of DH lines from superior S1 families and then evaluating their testcrosses in the second stage (S1TC-DHTC). For both breeding schemes, we examined different selection strategies, in which variance components and budgets varied, the cross and family structure was considered or ignored, and best linear unbiased prediction (BLUP) of testcross performance was employed. The specific objectives were to (1) maximize through optimum allocation of test resources the progress from selection, using the selection gain (ΔG) or the probability to select superior genotypes (P(q)) as well as their standard deviations as criteria, (2) investigate the effect of parental selection, varying variance components and budgets on the optimum allocation of test resources for maximizing the progress from selection, (3) assess the optimum filial generation (S0 or S1) for DH production, (4) compare various selection strategies - sequential selection considering or ignoring the cross and family structure - for maximizing progress from selection, (5) examine the effect of producing a larger number of candidates within promising crosses and S1 families on the progress from selection, and (6) determine the effect of BLUP, where information from genetically related candidates is integrated in the selection criteria, on the progress from selection. For both breeding schemes, the best strategy was to select among all S1 families and/or DH lines ignoring the cross structure. Further, in breeding scheme S1TC-DHTC, the progress from selection increased with variable sizes of crosses and S1 families, i.e., larger numbers of DH lines devoted to superior crosses and S1 families. Parental cross selection strongly influenced the optimum allocation of test resources and, consequently, the selection gain ΔG in both breeding schemes. With an increasing correlation between the mean testcross performance of the parental lines and the mean testcross performance of their progenies, the superiority in progress from selection compared to randomly chosen parents increased markedly, whereas the optimum number of parental crosses decreased in favor of an increased number of test candidates within crosses. With BLUP, information from genetically related test candidates resulted in more precise estimates of their genotypic values and the progress from selection slightly increased for both optimization criteria ΔG and P(q), compared with conventional phenotypic selection. Analytical solutions to enable fast calculations of the optimum allocation of test resources were developed. This analytical approach superseded matrix inversions required for the solution of the mixed model equations. In breeding scheme S1TC-DHTC, the optimum allocation of test resources involved (1) 10 or more test locations at both stages, (2) 10 or fewer parental crosses each with 100 to 300 S1 families at the first stage, and (3) 500 or more DH lines within a low number of parental crosses and S1 families at the second stage. In breeding scheme DHTC, the optimum number of test candidates at the first stage was 5 to 10 times larger, whereas the number of test locations at the first stage and the number of DH lines at the second stage was strongly reduced compared with S1TC-DHTC. The possibility to reduce the number of parental crosses by selection among parental lines is of utmost importance for the optimization of the allocation of test resources and maximization of the progress from selection. Further, the optimum allocation of test resources is crucial to maximize the progress from selection under given economic and quantitative-genetic parameters. By using marker information and BLUP-based genomic selection, more efficient selection strategies could be developed for hybrid maize breeding.