Application of nature-inspired optimization algorithms to improve the production efficiency of small and medium-sized bakeries

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.Die Steigerung der Produktionseffizienz durch die Optimierung von Arbeitsplänen ist eines der am meisten erforschten Themen im Bereich der Unternehmensplanung, die zur Entscheidungsfindung beiträgt. Es handelt sich dabei um die Aufteilung von Aufgaben auf die verfügbaren Ressourcen innerhalb der Beschränkungen einer Produktionsanlage mit dem Ziel der Kostenminimierung. Diese Optimierung von Arbeitsplänen wird mit Hilfe eines Modells durchgeführt, das die Aufgabenverteilung in der realen Welt mit Variablen und relevanten Einschränkungen nachbildet, um die Produktion zu simulieren. Zusätzlich zu einem Modell sind Optimierungsverfahren erforderlich, die bei der Bewertung und Verbesserung der Aufgabenverteilung helfen, um eine effiziente Gesamtproduktion zu erzielen. Das gesamte Verfahren wird in der Regel auf einem Computer durchgeführt, wobei diese beiden unterschiedlichen Komponenten (Modell und Optimierungsverfahren) zusammen einen Lösungsrahmen für die Produktionsplanung bilden und die Entscheidungsfindung in verschiedenen Fertigungsindustrien unterstützen. Kleine und mittelgroße Bäckereien haben zumeist keinen Zugang zu den modernsten Werkzeugen und die meisten ihrer Produktionspläne beruhen auf persönlichen Erfahrungen. Dies macht einen erheblichen Unterschied bei den Produktionskosten im Vergleich zu den großen Bäckereien aus, was sich in deren Marktdominanz widerspiegelt. In dieser Studie wird ein hybrides No-Wait-Flow-Shop-Modell vorgeschlagen, um einen Produktionsplan auf der Grundlage tatsächlicher Daten zu erstellen, der die Beschränkungen der Produktionsumgebung in kleinen und mittleren Bäckereien berücksichtigt. Mehrere einzel- und mehrzielorientierte, von der Natur inspirierte Optimierungsalgorithmen wurden implementiert, um effiziente Produktionspläne zu berechnen. Die Minimierung der Produktionsdauer ist das am häufigsten verwendete Qualitätskriterium für die Produktionseffizienz, da sie die Produktionskosten dominiert. Jedoch wird in Bäckereien durch hohe Leerlaufzeiten der Öfen Energie verschwendet was wiederum die Produktionskosten erhöht. Die Kombination beider Qualitätskriterien (minimale Produktionskosten, minimale Leerlaufzeiten der Öfen) ermöglicht eine zusätzliche Kostenreduzierung durch Energieeinsparungen und kurze Produktionszeiten. Um einen effizienten Produktionsplan zu erhalten, wurden daher die Minimierung der Produktionsdauer und der Ofenleerlaufzeit in die Optimierungsziele einbezogen. Um optimale Produktionspläne für bestehende Produktionsprozesse von Bäckereien zu ermitteln, wurden folgende Algorithmen untersucht: Particle Swarm Optimization, Simulated Annealing und Nawaz-Enscore-Ham. Die Methode der Gewichtung wurde verwendet, um zwei Ziele zu einem einzigen Ziel zu kombinieren. Die Optimierungsalgorithmen erwiesen sich als gut genug, um in angemessener Zeit optimale Pläne zu berechnen, wobei bei einem untersuchten Datensatz die Produktionsdauer um 29 % und die Leerlaufzeit des Ofens um 8 % reduziert wurde. Allerdings erwies sich die Konvergenz der Algorithmen als unzureichend, da nur mit einer geringen Wahrscheinlichkeit das beste oder nahezu beste Ergebnis berechnet wurde. Im Gegensatz dazu zeigte der in dieser Studie ebenfalls untersuchte modifizierte Particle-swarm-Optimierungsalgorithmus (mPSO) eine deutliche Verbesserung der Konvergenz mit einer höheren Wahrscheinlichkeit, bessere Ergebnisse zu erzielen im Vergleich zu den anderen Algorithmen. Um Kompromisse zwischen zwei Zielen zu erzielen, wurden moderne Algorithmen zur Mehrzieloptimierung implementiert: 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). Die Optimierungsalgorithmen ermöglichten eine effiziente Produktionsplanung mit einer Verringerung der Produktionsdauer um bis zu 12 % und einer Verringerung der Leerlaufzeit der Öfen um 26 % auf der Grundlage von Daten aus unterschiedlichen Produktionsprozessen. Der Leistungsvergleich zeigte signifikante Unterschiede zwischen diesen Mehrziel-Optimierungsalgorithmen, wobei NSGA-II am besten und OMOPSO und SMPSO am schlechtesten abschnitten. Die Gärung ist ein wichtiger Verarbeitungsschritt, der zur Qualität des Endprodukts beiträgt, indem der Geschmack und die Textur des Brotes positiv beeinflusst werden kann. Die Dauer der Gärung ist jedoch aufgrund der komplexen Interaktion von mehreren Größen abhängig wie der Hefezustand, der Temperatur in der Gärkammer und der chemischen Zusammensetzung des Mehls. Aufgrund der Variabilität der Gärzeit kann jedoch ein Produktionsplan, der auf die kürzeste Produktionszeit optimiert ist, sehr ineffizient sein. Die Berechnungsergebnisse zeigen, dass die Pläne mit der kürzesten und nahezu kürzesten Produktionsdauer eine erhebliche (bis zu 18 %) Erhöhung der Produktionsdauer aufgrund der Abweichung der Gärzeit von der erwarteten Dauer aufweisen. In dieser Arbeit wird eine Methode zur Entwicklung einer robusten Produktionsplanung vorgeschlagen, die Veränderungen in den Gärzeiten berücksichtigt, so dass selbst bei einer extremen Abweichung der Gärzeit die Schwankung der Produktionsdauer minimal ist. Die experimentellen Ergebnisse für einen Produktionsprozess ergaben einen robusten Produktionsplan, der nur 5 Minuten länger ist als die kürzeste Produktionsdauer, aber nur 21 Minuten in der Produktionsdauer schwankt, wenn die Gärzeit von -10 % bis +10 % der ermittelten Gärzeit variiert. In dieser Studie wird ein Vorgehen für kleine und mittlere Bäckereien vorgeschlagen, um ihre Produktionseffizienz in drei Schritten zu verbessern: Erfassung von Produktionsdaten, Simulation von Produktionsplänen mit dem hybrid No-Wait Flow Shop Modell und Ausführung der Optimierung. Für die Einzieloptimierung wird der mPSO-Algorithmus und für die Mehrzieloptimierung NSGA-II-Algorithmus empfohlen. Auf der Grundlage realer Bäckereiproduktionsdaten zeigten die Ergebnisse, dass die in den Bäckereien verwendeten Pläne ineffizient waren und mit Hilfe eines effizienten Optimierungsalgorithmus in einer angemessenen Rechenzeit optimiert werden konnten. Die Umsetzung eines solchen Vorgehens in kleinen und mittelgroßen Bäckereibetrieben trägt dazu bei effiziente und robuste Produktionspläne zu erstellen und somit die Wettbewerbsfähigkeit dieser Bäckereien zu erhöhen

Family influence on purchasing consumer home appliances: an empirical study in Dhaka city

BBA/201

Yield and morpho physical characters of some modern aus rice varieties at Khagrachari

Aus, aman and boro are three rice cultivating seasons in Bangladesh. Among these aus is the least cultivated and grown in comparatively small scale due to prevailing drought and less availability of surface water for irrigation. Modern varieties of aus rice cover a significant area of the country conversely local cultivars cover a small area. Aus rice requires much fewer inputs than aman and boro. Due to continuous declination of groundwater level, nowadays more emphasis is given on the extension of aus cultivation throughout the country. The present field study tested yield and morphological attributes of six developed aus rice varieties viz. Binadhan-14, Binadhan-19, BRRI dhan43, BRRI dhan48, BRRI dhan55 and BRRI dhan65 to characterize yield, maturity and phenological properties. The field trial was set at Satvaiyapara of Khagrachari during 2018 following Randomized Complete Block design with dispersed plots. All data were collected at harvest and analysed statistically by Statistix 10. Findings revealed that statistically highest grain yield was produced from BRRI dhan55 (4.49 t/ha) and BRRI dhan48 (4.48 t/ha); the lowest by BRRI dhan65 (3.06 t/ ha). The yield of Binadhan-19 (4.37 t/ha) and Binadhan-14 (3.87 t/ha) was intermediate. In case of maturity, Binadhan-19 (99.33 days) had the shortest life duration and BRRI dhan48 (113.67 days), the longest. The greater portion of the farmers was keen to grow Binadhan-19 and Binadhan-14 instead of BRRI dhan43 and BRRI dhan48 mainly for its short duration, optimal yield, long and slender quality grain. Binadhan-19 might be a promising aus variety in the Khagrachari hill tracts for gaining favourable yield within a short time. Therefore, further studies are needed in jhum cultivation with local cultivars for more significant comparison and acceptability to the rice farming community

Effect of long term fertilization on soil respiration and enzyme activities in floodplain soil

In agricultural farming system organic manuring and inorganic fertilizer application are the most common agricultural practices. Different fertilizer application lead to differences in soil nutrients, pH, and microbial species, which in turn affect the transformation and decomposition of organic carbon by soil microorganisms. Therefore, a laboratory incubation study was carried out to investigate the influence of long term manuring and fertilization on soil respiration by means of C mineralization and enzyme activities. A parallel first- and zero-order kinetic model was used to describe observed C mineralization in soil. The annual carbon mineralization was found to be significantly influenced by different fertilizer. This result indicates that more stable organic matter was formed in NP treated soil which is less prone to decomposition if present crop management has been changed. Other ward, NP has the highest potentiality to soil for the purpose of carbon sequestration in floodplain soil compared to other fertilizer. Urease activities varied from 4.7µg NH4-N/g soil/2h in NK treatment to 25.7µg NH4-N/g soil/2h in N+FYM treatment. N treatment had a significantly higher urease activity compared to the respective controls. When P, K, S and PK applied separately with N then the treatments show low enzyme activity to control and other treatments (N, N+FYM and NPKSZn). There were no significant differences for Arylamidase activities among the treatments. The arylamidase activities decreased when S applied in combination with N. On the other hand arylamidase activity increased with the application of all other treatment

Growth and development patterns in Mustard (Brassica spp.) as influenced by sowing time

Mustard is Bangladesh's leading oil crop, produced only during the winter (rabi) season. The sowing date is a key factor determining mustard's optimum growth and development. Because of global warming, gradual changes in season and weather parameters over time is creating a challenge in mustard cultivation. Thus, the present investigation assessed the role of different planting dates on several modern mustard varieties to disclose the optimum growth indicators necessary for elevated biological yield (BY) and harvest index (HI). Three planting times, viz. 31st October (D1), 10th November (D2),  20th November (D3) and six varieties viz. Binasarisha-4 (V1), Binasarisha-9 (V2), Binasarisha-10 (V3), BARI Sarisha-14 (V4), BARI Sarisha-16 (V5), BARI Sarisha-17 (V6) were put on a replicated factorial randomized complete block design (RCBD) during rabi 2019 at BINA Sub-station farm, Magura. At the final harvest stage, outcomes depicted that highest and lowest total dry mass (g/plant) was produced by treatment D3× V5 (64.03) and D1× V1 (15.34), maximum and minimum absolute growth rate (mg/plant/day) by D1× V5 (2389.10) and D2× V1 (184.50), most and least relative growth rate (mg/g/day) in D1× V4 (53.34) and D2× V1 (3.55), maximum and least crop growth rate (g/m2/day) with D1× V3 (55.60) and  D3× V4 (20.04). BY was the peak (8.13, 8.71, 8.77 t/ha) under all plantings (D1, D2, D3) with V5 variety, but HI (44.96%) was most in variety V4 with D2 sowing. Therefore, correlation studies showed a significant positive relationship between biological yield and harvest index. Overall, BARI Sarisha-16 performed well in all three sowing times, and remarkably, BY was rising with delayed planting in the case of Binasarisha-9, Binasarisha-10, and BARI Sarisha-14. This implies that delayed planting might not hamper yield but boost yield to some extent

ATM Shield: Analysis of Multitier Security Issues of ATM in the Context of Bangladesh

Over the last decade, consumers have been largely dependent on and trust the Automatic Teller Machine (ATM) to conveniently meet their banking needs. However, despite the numerous advantages of ATM system, ATM fraud has recently become more widespread. In this paper, we provide an overview of the possible fraudulent activities that may be perpetrated against ATMs and investigates recommended approaches to prevent these types of frauds. In particular, we develop a prototype model for the utilization of three tier security equipped ATM to provide security solutions against must of the well-known breaches. In this research article, the tools and techniques of ATM fraud are contemplated. A secure three layer electronic transaction mechanism of ATM is developed to prevent ATM frauds. In this three layer authentication systems the users can improve ATM security against frauds and crimes

Nutritional Profiling of Wild (Pangasius pangasius) and Farmed (Pangasius hypophthalmus) Pangasius Catfish with Implications to Human Health

publishedVersio

Smart detection and prevention procedure for DoS attack in MANET

A self-organized wireless communication short-lived network containing collection of mobile nodes is mobile ad hoc network (MANET). The mobile nodes communicate with each other by wireless radio links without the use of any pre-established fixed communication network infrastructure or centralized administration, such as base stations or access points, and with no human intervention. In addition, this network has potential applications in conference, disaster relief, and battlefield scenario, and have received important attention in current years. There is some security concern that increases fear of attacks on the mobile ad-hoc network. The mobility of the NODE in a MANET poses many security problems and vulnerable to different types of security attacks than conventional wired and wireless networks. The causes of these issues are due to their open medium, dynamic network topology, absence of central administration, distributed cooperation, constrained capability, and lack of clear line of defense. Without proper security, mobile hosts are easily captured, compromised, and attacked by malicious nodes. Malicious nodes behavior may deliberately disrupt the network so that the whole network will be suffering from packet losses. One of the major concerns in mobile ad-hoc networks is a traffic DoS attack in which the traffic is choked by the malicious node which denied network services for the user. Mobile ad-hoc networks must have a safe path for transmission and correspondence which is a serious testing and indispensable issue. So as to provide secure communication and transmission, the scientist worked explicitly on the security issues in versatile impromptu organizations and many secure directing conventions and security measures within the networks were proposed. The goal of the work is to study DoS attacks and how it can be detected in the network. Existing methodologies for finding a malicious node that causes traffic jamming is based on node’s retains value. The proposed approach finds a malicious node using reliability value determined by the broadcast reliability packet (RL Packet). In this approach at the initial level, every node has zero reliability value, specific time slice, and transmission starts with a packet termed as reliability packet, node who responded properly in specific time, increases its reliability value and those nodes who do not respond in a specific time decreases their reliability value and if it goes to less than zero then announced that it’s a malicious node. Reliability approach makes service availability and retransmission time

Validated Molecular Marker for Downy Mildew Disease Resistance Breeding of Sunflower: A Short Review

The oomycete pathogen Plasmopara halstedii responsible for sunflower downy mildew (DM), that is a significant and important disease that greatly affects the economy. As of now, there is no non-race-specific resistance for this disease and breeders are depended on race-specific resistance to control DM disease. On the other hand, using conventional breeding procedure introgression of the DM resistance genes is a long-term task due to the highly virulent and aggressive nature of the P. halstedii pathogen. Molecular markers that can be applied at the seedling stage, offers rapid response for selection with higher precision as well as a lower cost. There are currently 36 downy mildew resistance genes (R genes), designated as Pl (Pl1-Pl36, Plhra, and PlArg, in sunflowers, each with a unique linkage group (LGs). The availability of DM resistance genomic data of sunflower, related to Single Nucleotide Polymorphisms (SNP) based markers with mine allelic diversity maximize the opportunity of utilizing Marker assisted selection (MAS) techniques for downy mildew resistance breeding. This review highlights the available genetic marker and their utilization at MAS techniques for enhancing downy mildew disease resistant breeding program of sunflowers

Adjusting planting time of Binadhan-17 in boro season

Boro rice (grown in winter under irrigated condition) contributes to the major portion of rice production (over 50%) in Bangladesh. Binadhan-17 is a green super rice developed by BINA which requires 30% less nitrogenous fertilizer and water which is grown in aman season (primely produced under rainfed). Due to it’s increasing popularity and adoption rice growers are keen to cultivate it in boro season also. Taking account of the above situation, two field trials were conducted at Magura during November 2019 to May 2020 to investigate the effect of variety, sowing dates and their interaction. Factorial RCBD (Randomized Complete Block Design) was applied for experimentation. Two rice varieties: Binadhan-17 (V1), BRRI dhan58 (V2) and three sowing times: 30th November (T1), 10th December (T2), 20th December (T3) were used as treatments. 35 days old seedlings were transplanted in main field. Relevant agronomic and morphological data were statistically analyzed through Statistix 10.0. Combined effect of the above factors at farm exposed that, T1×V1 required longest days (159.33 days) to mature. but, comparatively short life cycle (149.97 days) was observed by T3×V2. Maximum grain was yielded (7.70 t/ha) by T2×V1 and minimum (5.74 t/ha) by T1×V1 treatment combination. Outcomes of on station revealed that, T1×V1 needed more days (158.00 days) to mature; conversely, alike duration was noted with T2×V2 (147.20 days) and T3×V2 (145.43 days) which matured quite earlier. T2×V1 produced the highest grain yield (7.41 t/ha) and T1×V2 the lowest (5.94 t/ha). Our results indicate that, planting of Binadhan-17 on 10th December may give insect-disease free grains with optimum yield in context of Magura region. Farmers will be financially benefited if they cultivate this variety in the boro season in lieu of aman; due to higher yiel