somnath maji - Academia.edu (original) (raw)
Papers by somnath maji
Expert Systems With Applications, Jun 1, 2023
The COVID-19 pandemic has spread worldwide exponentially. Typically, for testing, a provincial ma... more The COVID-19 pandemic has spread worldwide exponentially. Typically, for testing, a provincial main government hospital cum testing center collects patients' specimens from remote health centers in the minimum possible time, satisfying the 'false negativity' constraint of the first collected specimen. With infrastructural developments throughout the world, multiple paths are available for transportation between two cities. Currently, the 'green corridor' is used for the transportation of human organs to be implanted, travel of VIPs, etc., in the minimum possible time. Taking these facts in consideration, for the first time, a green corridor system is suggested to provide a transportation pathway from small hospitals and urban/rural health centers to the testing center with COVID-19 specimens such as blood, nasal and throat swabs, and viral RNA, within the first collected specimen's life period. As health centers are located in different places, appropriate routing plans are needed for visiting them in the minimum possible time. A problem arises if this routing time exceeds the 'false negativity' of the first collected specimen. Thus, multipath COVID-19 specimen collection problems (MPC-19SCPs) are mathematically formulated to be collected from all health centers, and optimum routing plans are obtained using fixed and variable length genetic algorithms (VLGAs) developed for this purpose. For the first time, green corridor systems are suggested to incorporate the centers. The objectives of the models are, subject to the 'false-negative'' constraint, minimization of the system time (Model A) and the green corridor time without or with mutual cooperation among the minimum number of centers for the transfer of specimens (Models B and C, respectively). The developed algorithms are based on variable length chromosomes, probabilistic selection, comparison crossover and generation-dependent mutation. Some benchmark instances from TSPLIB are solved by VLGA and GA. The competitiveness of VLGA is established through ANOVA. The models are numerically demonstrated, and some conclusions are derived.
Expert Systems With Applications, Nov 1, 2023
In developing countries, 40 percent of fresh fruits and vegetables are generally transported thro... more In developing countries, 40 percent of fresh fruits and vegetables are generally transported through nonrefrigerated vehicles and perishes before use, and wholesalers lose potential profits due to item rot. Here, a wholesaler's conveyance with fresh goods starts from a depot and returns to it after dropping the amounts at nodes (retailers) as per previously placed orders. As a perishable item's freshness (color and texture) changes with time, the item's selling price depends on its freshness at the time of delivery to retailers. There are multiple route connections among retailers and depots. Due to fatigue, the driver takes 15 minutes to rest after every two hours during the journey; otherwise, they are at risk of becoming overtired. Under these circumstances, multiroute fresh produce green routing models (MrFPGRMs) are formulated considering the product's freshness, optimum routing plan, appropriate routes, sales revenue, vehicle's running cost and speed, costs and times due to transportation and unloading, fixed charges, greenness (fuel cost), driver's salary and fatigue. The objective is to find the optimum routing plan, best-suited routes between the nodes, and vehicle velocity for the wholesaler's maximum profit, minimum fuel cost, or both. Virgin discrete fireworks algorithms are developed for the solution based on Type-1 and Type-2 fuzzy logic (T1FLDFWA and T2FLDFWA). Numerical experiments are performed through the T2FLDFWA for two time-dependent freshness functions, one of which is new. The results against driver rest, no rest, continuous journey risk, and a trade-off between profit and greenness are presented. Pareto fronts for multiobjectives are depicted. Some managerial decisions are observed.
Soft Computing Research Society eBooks, 2021
Decision Analytics Journal
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Smart innovation, systems and technologies, Nov 29, 2022
Elsevier, 2022
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
In this investigation, we propose a modified teaching-learning-based optimization algorithm (mTLB... more In this investigation, we propose a modified teaching-learning-based optimization algorithm (mTLBO) for solving the traveling salesman problems. We design an mTLBO with Boltzmann selection, novel upgradation strategy in the teaching phase, and interactive group-based crossover for learners in the learning phase. In the teaching phase, we focus on different learning abilities of different subjects of individual learners and in the learning phase, learners are randomly divided to form different groups; it helps to maintain the diversity of the population and to avoid premature convergence. The proposed algorithm is tested against benchmark functions from TSPLIB. The results are compared with the proposed mTLBO, TLBO and standard Genetic Algorithm with Roulette wheel selection, cyclic crossover and random mutation. The effectiveness of the proposed algorithm is shown through statistical test ANOVA.
Expert Systems With Applications, Jun 1, 2023
The COVID-19 pandemic has spread worldwide exponentially. Typically, for testing, a provincial ma... more The COVID-19 pandemic has spread worldwide exponentially. Typically, for testing, a provincial main government hospital cum testing center collects patients' specimens from remote health centers in the minimum possible time, satisfying the 'false negativity' constraint of the first collected specimen. With infrastructural developments throughout the world, multiple paths are available for transportation between two cities. Currently, the 'green corridor' is used for the transportation of human organs to be implanted, travel of VIPs, etc., in the minimum possible time. Taking these facts in consideration, for the first time, a green corridor system is suggested to provide a transportation pathway from small hospitals and urban/rural health centers to the testing center with COVID-19 specimens such as blood, nasal and throat swabs, and viral RNA, within the first collected specimen's life period. As health centers are located in different places, appropriate routing plans are needed for visiting them in the minimum possible time. A problem arises if this routing time exceeds the 'false negativity' of the first collected specimen. Thus, multipath COVID-19 specimen collection problems (MPC-19SCPs) are mathematically formulated to be collected from all health centers, and optimum routing plans are obtained using fixed and variable length genetic algorithms (VLGAs) developed for this purpose. For the first time, green corridor systems are suggested to incorporate the centers. The objectives of the models are, subject to the 'false-negative'' constraint, minimization of the system time (Model A) and the green corridor time without or with mutual cooperation among the minimum number of centers for the transfer of specimens (Models B and C, respectively). The developed algorithms are based on variable length chromosomes, probabilistic selection, comparison crossover and generation-dependent mutation. Some benchmark instances from TSPLIB are solved by VLGA and GA. The competitiveness of VLGA is established through ANOVA. The models are numerically demonstrated, and some conclusions are derived.
Expert Systems With Applications, Nov 1, 2023
In developing countries, 40 percent of fresh fruits and vegetables are generally transported thro... more In developing countries, 40 percent of fresh fruits and vegetables are generally transported through nonrefrigerated vehicles and perishes before use, and wholesalers lose potential profits due to item rot. Here, a wholesaler's conveyance with fresh goods starts from a depot and returns to it after dropping the amounts at nodes (retailers) as per previously placed orders. As a perishable item's freshness (color and texture) changes with time, the item's selling price depends on its freshness at the time of delivery to retailers. There are multiple route connections among retailers and depots. Due to fatigue, the driver takes 15 minutes to rest after every two hours during the journey; otherwise, they are at risk of becoming overtired. Under these circumstances, multiroute fresh produce green routing models (MrFPGRMs) are formulated considering the product's freshness, optimum routing plan, appropriate routes, sales revenue, vehicle's running cost and speed, costs and times due to transportation and unloading, fixed charges, greenness (fuel cost), driver's salary and fatigue. The objective is to find the optimum routing plan, best-suited routes between the nodes, and vehicle velocity for the wholesaler's maximum profit, minimum fuel cost, or both. Virgin discrete fireworks algorithms are developed for the solution based on Type-1 and Type-2 fuzzy logic (T1FLDFWA and T2FLDFWA). Numerical experiments are performed through the T2FLDFWA for two time-dependent freshness functions, one of which is new. The results against driver rest, no rest, continuous journey risk, and a trade-off between profit and greenness are presented. Pareto fronts for multiobjectives are depicted. Some managerial decisions are observed.
Soft Computing Research Society eBooks, 2021
Decision Analytics Journal
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Smart innovation, systems and technologies, Nov 29, 2022
Elsevier, 2022
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
In this investigation, we propose a modified teaching-learning-based optimization algorithm (mTLB... more In this investigation, we propose a modified teaching-learning-based optimization algorithm (mTLBO) for solving the traveling salesman problems. We design an mTLBO with Boltzmann selection, novel upgradation strategy in the teaching phase, and interactive group-based crossover for learners in the learning phase. In the teaching phase, we focus on different learning abilities of different subjects of individual learners and in the learning phase, learners are randomly divided to form different groups; it helps to maintain the diversity of the population and to avoid premature convergence. The proposed algorithm is tested against benchmark functions from TSPLIB. The results are compared with the proposed mTLBO, TLBO and standard Genetic Algorithm with Roulette wheel selection, cyclic crossover and random mutation. The effectiveness of the proposed algorithm is shown through statistical test ANOVA.