Evolutionary Algorithms for Resource Constrained Project Scheduling Problems

The resource constrained project scheduling problems (RCPSPs) are well-known challenging research problems that require efficient solutions to meet the planning need of many practical high-value projects. RCPSPs are usually solved using optimization problem-solving approaches. In recent years, evolutionary algorithms (EAs) have been extensively employed to solve optimization problems, including RCPSPs. Despite that numerous EAs have been developed for solving various RCPSPs, there is no single algorithm that is consistently effective across a wide range of problems. In this context, this thesis aims to propose a few new algorithms for solving different RCPSPs that include singular-resource and multiple-resource problems with single and multiple objectives. In general, RCPSPs are solved with an assumption that its activities are homogeneous, where all activities require all resource types. However, many activities are often singular, requiring only a single resource to complete an activity. Even though the existing algorithms that were developed for multi-resource problems, can solve this RCPSP variant with minor modifications, they are computationally expensive because they include some unnecessary resource constraints in the optimization process. In this thesis, at first, a problem with singular resource and single objective is considered. A heuristic-embedded genetic algorithm (GA) has been proposed for solving this problem, and it's effectiveness has been investigated. To enhance the performance of this algorithm, three heuristics are proposed and integrated with it. As there are no test problems available for singular resource problems, new benchmark problems are generated by modifying the existing multi-resource RCPSPs test set. As compared with experimental results of one of the modified algorithms and an exact solver, it was shown that the proposed algorithm achieved a better quality of solution while requiring a significantly smaller computational budget. The proposed algorithm is then extended to make it suitable for solving multi-resource cases with a single objective, which are known as traditional RCPSPs. A self-adaptive GA is developed for this problem. The proposed self-adaptive component of the algorithm selects an appropriate genetic operator based on their performance as the evolution progresses and increases. To judge the performance of this algorithm, small to large-scale problem instances have been solved from the PSP Library and the results are compared with state-of-the-art algorithms. Based on the experimental results, it was found that the proposed algorithm was able to obtain much better solutions than the non-self-adaptive GA. Furthermore, the proposed approach outperformed the state-of-the-art algorithms. In practice, cost of some resources varies with the day of the week or specific days in the month or year. To consider these day dependent costs, a new cost function is developed that is integrated with the usual cost fitness function in a multi-objective version of RCPSPs. Completion time is considered as the second objective. A heuristic-embedded self-adaptive multi-objective GA is proposed for both singular and multi-resource problems. In this algorithm, the selection mechanism is based on crowding distance and a reference point. A customized mutation operator is also introduced. The experimental results show that the proposed variant, with reference points-based selection, outperformed the variant, with crowding distance-based selection. In many situations, resource availability varies with time, such as time of the day and in some particular days. A dynamic multi-operators-based GA is proposed to deal with this variant. Along with the genetic operators, two local search methods are also included in the self-adaptive mechanism. The proposed approach has been validated using both large-scale singular and multi-resource problem instances with a single objective. Its experimental results demonstrate the efficiency of the proposed dynamic multi-operator-based approach. In summary, the proposed algorithms can solve different variants of RCPSPs that cover a broad spectrum of project scheduling problems, with significantly less computational tim

ISTRAŽIVANJE GENETSKE VARIJABILNOSTI ZA SELEKCIJU ELITNE GERMPLAZME U SEZAMU (Sesamum indicum L.)

Sesame (Sesamum indicum L.) is one of the oldest oilseed crops and important for high nutritional quality as well as medicinal value. Fifty diverse sesame genotypes were evaluated to study genetic variability. The results revealed that the genotypes were a significant variation in most of the studied characters. In all cases, the phenotypic variances were much higher than genotypic variances suggests a higher level of the environmental effect on the expression of these characters. The highest genotypic coefficient of variations (GCV) was observed in seed yield per plant while the highest heritability was exhibited by hundred seed weight followed by days to 80% maturity, pods per plant, number of branches per plant and seed yield per plant. The genotypic correlation with seed yield per plant showed a significantly strong positive with days to 50% flowering, plant height and number of pods per plant at both the genotypic and phenotypic level. The path coefficient analysis showed that pods per plant and seeds per pod were the most important contributing traits to seed yield. The 50 sesame genotypes were grouped into five clusters. The highest inter-cluster distance was observed between the cluster III and V while the lowest inter-cluster distance was observed between the cluster III and IV. Among 50 sesame genotypes G7, G36, G38 and G46 might be suggested for future hybridization program for the improvement of sesame yield.Sezam (Sesamum indicum L.) je jedan od najstarijih usjeva uljarica i važan zbog visoke hranidbene kakvoće kao i medicinske vrijednosti. Procijenjeno je pedeset različitih genotipova sezama po genetskoj varijabilnosti. Rezultati su pokazali da su genotipovi značajna varijacija u većini proučavanih karakteristika. U svim slučajevima fenotipske varijance bile su mnogo više nego genotipske varijance što upućuje na višu razinu djelovanja okoline na izražavanje tih karakteristika. Najviši genotipski koeficijent varijacija primijećen je za prinos sjemena po biljki dok je najviša heretabilnost u težini sto sjemenki zatim po danima do 80% zrelosti, mahuna po biljci, broju granćica po biljci i sjemena po biljci. Genotipska korelacija s prinosom sjemena po biljci bila je značajno vrlo pozitivna s danima do 50% cvjetanja, visinom biljke i brojem mahuna po biljci na genotipskoj i fenotipskoj razini. Prema analizi koeficienata broj mahuna po biljci i prinos sjemena po mahuni bili su najvažniji doprinos prinosu sjemena. Pedeset genotipova sezama svrstano je u pet klastera. Najveća udaljenost među klasterima primijećena je između klastera III i IV. Među 50 sezama genotipovi G7, G36, G38 i G46 mogu se predložiti za budući program hibridizacije za poboljšanje prinosa sezama

変遷の中で : 多国的、多文化的時代での移住者の美術家における逆説的烈火の光景 : 自作品におけるデシ概念とサブカルチャー的表現の考察

東京藝術大学平成22年

PROCJENA GENETSKOG ODSTUPANJA MEĐU NAPREDNIM LINIJAMA BRASSICAE NAPUS L

A field experiment was conducted with 22 Brassica napus L. advanced lines at the experimental farm of Sher-e-Bangla Agricultural University, Dhaka to study the genetic variation among advanced lines of Brassica napus L. during November 2008 to March 2009. The genotypes were significantly different for all the characters studied except for days to 80% maturity. The characters days to 80% maturity, plant height, number of primary branches per plant, number of seeds per siliqua, number of siliqua per plant and seed yield per plant showed higher influence of environment whereas, siliqua length and 1000-seed weight showed the least. Moreover, the number of primary branches per plant, number of secondary branches per plant, siliqua length, number of seeds per siliqua, number of siliqua per plant, 1000-seed weight and seed yield per plant showed moderate broad base heritability while plant height exhibited the highest heritability. The significant positive correlation with seed yield per plant was found in plant height, number of primary branches per plant and number of siliqua per plant. However, the highest significant positive correlation was found between days to 50% flowering and plant height. Path coefficient analysis showed that the plant height had maximum positive direct effect on seed yield followed by number of siliqua per plant and siliqua length. Plant height, number of primary branches per plant and number of siliqua per plant were the most important contributors to seed yield per plant which could be taken into consideration in future hybridization program.Od studenog 2008. do ožujka 2009. obavljeni su poljski pokusi s 22 napredne linije Brassicae napus L. na pokusnoj farmi Sher-e-Bangla Poljoprivrednog fakulteta u Dhaki, radi istraživanja genetskog odstupanja među naprednim linijama Brassicae napus L. Genetski su se značajno razlikovale u svim istraživanim značajkama osim dana do 80% zrelosti. Značajke dana do 80% zrelosti, visina biljke, broj primarnih grančica po biljci, broj sjemenki po komušci, broj komušaka po biljci i prinos sjemena po biljci pokazale su veći utjecaj okoline dok su duljina komuške i težina 1000-sjemenki pokazali najmanji. Osim toga, broj primarnih grančica po biljci, broj sekundarnih grančica po biljci, duljina komuške, broj sjemenki po komušci, broj komušaka po biljci, težina 1000-sjemenki i prinos sjemena po biljci pokazali su umjereno široku osnovnu nasljednost, dok je visina biljke pokazala najveću nasljednost. Značajna pozitivna korelacija s prinosom sjemena po biljci nađena je u visini biljke, broju primarnih grančica po biljci i broju komušaka po biljci. Međutim, najviša značajna pozitivna korelacija nađena je između dana do 50% cvjetanja i visine biljke. Analiza koeficijenta kretanja pokazala je da je visina biljke maksimalno pozitivno direktno djelovala na prinos sjemena i zatim na broj komušaka po biljci i duljinu komušaka.Visina biljke, broj primarnih grančica po biljci i broj komušaka po biljci bili su najvažniji pomagači za prinos sjemena po biljci, što treba uzeti u obzir u budućem programu hibridizacije

Multivariate Analysis of Genetic Variation in Rapeseed ( Brassica Napus L. )

Designing breeding programs for rapeseed (Brassica napus L.) cultivars with developed seed and oil yields needs information about the genetic variability of characters. In this study, 40 rapeseed genotypes were evaluated for genetic variation and relationships between 12 agro-morphological characters. Brassica species represent a broad range of crops. This redirects the high degree of genetic diversity and allied phenotypic plasticity. Significant differences among the clusters were observed. The first two components with Eigen value were greater than unity contributed a total of 42.77% variation to the divergence. The genotypes were grouped into five clusters. Cluster V contained the maximum number of genotypes (11) and cluster III contained the lowest (4). The highest inter-cluster distance was found between cluster II and cluster V and the lowest between cluster II and cluster IV. The highest intra-cluster distance was noticed for cluster I and the lowest for cluster V. Considering diversity pattern and other agronomic performance lines Nap0837, Nap-0733-1, Nap-2066, Nap-9901, Nap-108 and BARI-8 could be considered apposite parents. This information is suitable for hybrid breeding and encouraging breeders to exchange their germplasm as to enlarge the genetic diversity of breeding accessions

Genetic Divergence in Advanced Lines of Oilseed Rape (Brassica napus ssp oleifera L.)

A field experiment was conducted with 22 Brassica napus L. advanced lines at the experimental farm of Sher-e-Bangla Agricultural University, Dhaka from November 2008 to March 2009 to asses genetic diversity among advanced lines of Brassica napus L. Different multivariate analysis techniques were used to classify 22 Brassica napus genotypes. The genotypes were grouped into four clusters. The highest inter-cluster distance was observed between clusters II and IV whereas the maximum intra-cluster distance was found in cluster II. Therefore, the genotypes belonging to cluster I and cluster II, cluster II and cluster III and cluster III and cluster IV have been selected for future hybridization program. The role of number of secondary branches per plant and number of siliqua per plant in both vectors were important components for genetic divergence in these materials. Considering group distance and other agronomic performance the inter-genotypic crosses between G1 and G2, G2 and G6; G6 and G7; G6 and G8 and G7 and G8 might be suggested for future hybridization program

Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities

Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.This research was supported by Water Aid Bangladesh, North South University, Dhaka, COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University (NSTU), Noakhali, Bangladesh, the International Training Network of Bangladesh University of Engineering and Technology (ITN-BUET) - Centre for Water Supply and Waste Management, and KTH Royal Institute of Technology, Sweden. We acknowledge the sincere help and support of the staff and volunteers of NSTU-COVID-19 Diagnostic Lab, Noakhali Science and Technology University, Bangladesh during the different phases of the study. PB and MTI acknowledge the Life Science Technology Platform, Science for Life Laboratory for the seed funding to initiate the wastewater-based epidemiological studies for SARS-CoV-2 in Bangladesh. We would also like to acknowledge the two anonymous reviewers for their critical comments as well as their thoughtful insights, which has significantly improved the manuscript.Peer reviewe