The integrated circuit (IC) manufacturing process is capital intensive and complex. The production process of unit product (or die, as it is commonly referred to) takes several weeks. Semiconductor factories (fabs) co...The integrated circuit (IC) manufacturing process is capital intensive and complex. The production process of unit product (or die, as it is commonly referred to) takes several weeks. Semiconductor factories (fabs) continuously attempt to improve their productivity, as measured in output and cycle time (or mean flow time). The conflicting objective of producing maximum units at minimal production cycle time and at the highest quality, as measured by die yield, is discussed in this paper. The inter-related effects are characterized, and a model is proposed to address this multi-objective function. We then show that, with this model, die cost can be optimized for any given operating conditions of a fab. A numerical example is provided to illustrate the practicality of the model and the proposed optimization method.展开更多
Imaging department is an important department of a hospital contributing directly to patient care, providing diagnostic support to all specialties which cannot practice efficiently without their support. Hospital admi...Imaging department is an important department of a hospital contributing directly to patient care, providing diagnostic support to all specialties which cannot practice efficiently without their support. Hospital administrators are looking for newer tools to control costs without affecting the quality of patient care. It is well known that the escalation of costs for advanced technology has been dramatic and it has been labeled as one of the culprits for great increase in healthcare costs. A prospective study for a period of six months was carried out for calculation of unit cost of radiological investigations CT head, CT chest, CT abdomen and MRI. Unit costs were computed under direct and indirect costs. The actual cost incurred by the hospital on CT head was Rupees 581.40 (US $10.89), CT abdomen Rupees 2339.20 (US $43.83), CT chest Rupees 2339.20 (US $43.83), and MRI Rupees 4497.50 (US $84.28). However, in the hospital patients are charged Rupees 900 (US $16.86) for CT head, Rupees 1200 (US $22.48) for CT abdomen, Rupees 1200 (US $22.48) for CT chest and Rupees 2500 (US $46.85) for MRI. There is a substantial loss of revenue because of subsidies provided to patients in a tertiary care teaching hospital which needs revision of charges.展开更多
This paper presents a new approach via composite cost function to solve the unit commitment problem. The unit com-mitment problem involves determining the start-up and shut-down schedules for generating units to meet ...This paper presents a new approach via composite cost function to solve the unit commitment problem. The unit com-mitment problem involves determining the start-up and shut-down schedules for generating units to meet the fore-casted demand at the minimum cost. The commitment schedule must satisfy the other constraints such as the generating limits, spinning reserve, minimum up and down time, ramp level and individual units. The proposed algorithm gives the committed units and economic load dispatch for each specific hour of operation. Numerical simulations were carried out using three cases: four-generator, seven-generator, and ten-generator thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as Dynamic programming, Branch and bound, Ant colony system, and traditional Tabu search. The result demonstrated the accuracy of the proposed method.展开更多
This paper deals with a Unit Commitment (UC) problem of a power plant aimed to find the optimal scheduling of the generating units involving cubic cost functions. The problem has non convex generator characteristics, ...This paper deals with a Unit Commitment (UC) problem of a power plant aimed to find the optimal scheduling of the generating units involving cubic cost functions. The problem has non convex generator characteristics, which makes it very hard to handle the corresponding mathematical models. However, Teaching Learning Based Optimization (TLBO) has reached a high efficiency, in terms of solution accuracy and computing time for such non convex problems. Hence, TLBO is applied for scheduling of generators with higher order cost characteristics, and turns out to be computationally solvable. In particular, we represent a model that takes into account the accurate higher order generator cost functions along with ramp limits, and turns to be more general and efficient than those available in the literature. The behavior of the model is analyzed through proposed technique on modified IEEE-24 bus system.展开更多
文摘The integrated circuit (IC) manufacturing process is capital intensive and complex. The production process of unit product (or die, as it is commonly referred to) takes several weeks. Semiconductor factories (fabs) continuously attempt to improve their productivity, as measured in output and cycle time (or mean flow time). The conflicting objective of producing maximum units at minimal production cycle time and at the highest quality, as measured by die yield, is discussed in this paper. The inter-related effects are characterized, and a model is proposed to address this multi-objective function. We then show that, with this model, die cost can be optimized for any given operating conditions of a fab. A numerical example is provided to illustrate the practicality of the model and the proposed optimization method.
文摘Imaging department is an important department of a hospital contributing directly to patient care, providing diagnostic support to all specialties which cannot practice efficiently without their support. Hospital administrators are looking for newer tools to control costs without affecting the quality of patient care. It is well known that the escalation of costs for advanced technology has been dramatic and it has been labeled as one of the culprits for great increase in healthcare costs. A prospective study for a period of six months was carried out for calculation of unit cost of radiological investigations CT head, CT chest, CT abdomen and MRI. Unit costs were computed under direct and indirect costs. The actual cost incurred by the hospital on CT head was Rupees 581.40 (US $10.89), CT abdomen Rupees 2339.20 (US $43.83), CT chest Rupees 2339.20 (US $43.83), and MRI Rupees 4497.50 (US $84.28). However, in the hospital patients are charged Rupees 900 (US $16.86) for CT head, Rupees 1200 (US $22.48) for CT abdomen, Rupees 1200 (US $22.48) for CT chest and Rupees 2500 (US $46.85) for MRI. There is a substantial loss of revenue because of subsidies provided to patients in a tertiary care teaching hospital which needs revision of charges.
文摘This paper presents a new approach via composite cost function to solve the unit commitment problem. The unit com-mitment problem involves determining the start-up and shut-down schedules for generating units to meet the fore-casted demand at the minimum cost. The commitment schedule must satisfy the other constraints such as the generating limits, spinning reserve, minimum up and down time, ramp level and individual units. The proposed algorithm gives the committed units and economic load dispatch for each specific hour of operation. Numerical simulations were carried out using three cases: four-generator, seven-generator, and ten-generator thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as Dynamic programming, Branch and bound, Ant colony system, and traditional Tabu search. The result demonstrated the accuracy of the proposed method.
文摘This paper deals with a Unit Commitment (UC) problem of a power plant aimed to find the optimal scheduling of the generating units involving cubic cost functions. The problem has non convex generator characteristics, which makes it very hard to handle the corresponding mathematical models. However, Teaching Learning Based Optimization (TLBO) has reached a high efficiency, in terms of solution accuracy and computing time for such non convex problems. Hence, TLBO is applied for scheduling of generators with higher order cost characteristics, and turns out to be computationally solvable. In particular, we represent a model that takes into account the accurate higher order generator cost functions along with ramp limits, and turns to be more general and efficient than those available in the literature. The behavior of the model is analyzed through proposed technique on modified IEEE-24 bus system.
