Electric vehicles charging stations are capital intensive and time consuming. It is necessary to optimize resources to make fast charging a viable and easily available option. To solve this problem, we use statistical...
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Electric vehicles charging stations are capital intensive and time consuming. It is necessary to optimize resources to make fast charging a viable and easily available option. To solve this problem, we use statistical approaches to identify a near-optimal solution in distributing an EV charging network over a large geographical region. Based on principles of linear programming and Bayesian theory, an improved EV charging distribution network is proposed that considers socio-economic parameters. Finally, the numerical results are presented, using these mathematical principles; it is shown that the impact on grid can be minimized while providing a safe and cost-effective EV Charging infrastructure.
We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (QoS) constraints. The key challenge lies in the fact that the ...
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ISBN:
(纸本)9781665476621
We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (QoS) constraints. The key challenge lies in the fact that the QoS functions have no closed-form and need to be approximated by simulation. In this paper we propose a new way to approximate the QoS functions by logistic functions and design a new algorithm that combines logistic regression, cut generations and logistic-based local search to efficiently find good staffing solutions. We report computational results using examples up to 65 call types and 89 agent groups showing that our approach performs well in practice, in terms of solution quality and computing time.
Secret sharing is a central topic in information-theoretical cryptography. In a secret sharing scheme a random secret is distributed among participants so that only the qualified subsets of parties can recover the sec...
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ISBN:
(数字)9781665421591
ISBN:
(纸本)9781665421607
Secret sharing is a central topic in information-theoretical cryptography. In a secret sharing scheme a random secret is distributed among participants so that only the qualified subsets of parties can recover the secret. In this paper we improve previously known [13] lower bounds on the size of the largest share for several specific access structures. Our approach is based on non-Shannon-type information inequalities. We employ the linear programming (LP) technique that permits to apply new information inequalities indirectly. To reduce computational complexity of the involved linear programs we extensively use symmetry considerations.
Instances generation is crucial for linear programming algorithms, which is necessary either to find the optimal pivot rules by training learning method or to evaluate and verify corresponding algorithms. This study p...
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Lower and upper bounds on the union probability for N events are derived in terms of the individual and pairwise event probabilities by solving a linear program with variables. The bounds, which can be efficiently det...
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Lower and upper bounds on the union probability for N events are derived in terms of the individual and pairwise event probabilities by solving a linear program with variables. The bounds, which can be efficiently determined, are shown to be optimal when and are always sharper than recent optimal bounds which use slightly less information. Their competitive sharpness is also illustrated via numerical comparisons with state-of-the-art bounds in the literature.
The provision of electricity through renewable energy sources have become the pivot for sustainable development in most remote rural communities. This paper presents the optimal power dispatch of an off-grid hybrid en...
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ISBN:
(数字)9781665455053
ISBN:
(纸本)9781665455060
The provision of electricity through renewable energy sources have become the pivot for sustainable development in most remote rural communities. This paper presents the optimal power dispatch of an off-grid hybrid energy system which consists of a solar PV, wind energy and small hydropower system. linear programming technique is proposed to solve the optimization problem. The objective of the optimization problem is to minimize the cost of electricity taking into account the constraints of the hybrid energy system. A case study for a remote rural community in Zimbabwe is used for this study. The results show that the off-grid renewable energy system is able to supply the load demand of the rural community and it is therefore a feasible solution for energy provision in remote rural communities.
Scientists often must simultaneously localize and discover signals. For instance, in genetic fine-mapping, high correlations between nearby genetic variants make it hard to identify the exact locations of causal varia...
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Based on the existing pivot rules, the simplex method for linear programming is not polynomial in the worst case. Therefore the optimal pivot of the simplex method is crucial. This study proposes the optimal rule to f...
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Fast-food chains often offer delivery services. Adding this service will add costs for the fast-food chains. Route distance optimization is a common strategy to minimize costs for transportation problems. Delivery sys...
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Fast-food chains often offer delivery services. Adding this service will add costs for the fast-food chains. Route distance optimization is a common strategy to minimize costs for transportation problems. Delivery system and assignment can be seen as a transportation problem. A model can be solved using the linear programming approach given the proper variables, constraints, and equations. This paper aims to present a solution to optimize delivery assignments for different branches to minimize cost. The Mixed Integer linear programming Model is used in this paper as the method to compute for linear programming. The model was simulated using MATLAB Software. The objective function seeks to minimize the transportation cost of delivery by optimizing the distance between the fast-food chain branches and the customer houses. Constraints and variables were considered, such as the number of products sold and the production capacity of each store. The initial results showed that orders could be assigned to a farther branch to keep up with constraints and optimize the delivery process.
Eating a well-balanced diet is as important as exercising the body to remain healthy and avoid any sickness. A healthy diet is especially important for students who use their minds and body to accomplish tasks in thei...
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Eating a well-balanced diet is as important as exercising the body to remain healthy and avoid any sickness. A healthy diet is especially important for students who use their minds and body to accomplish tasks in their daily classes. With this, it is important to prepare a well-balanced meal for them to get the right amount of nutrients in their body. Additionally, making these meals more affordable is necessary to make them more accessible for the students. Hence, this study aims to optimize the cost of a one-week cycle menu from breakfast to dinner for college students to satisfy the nutrients their body needs using different linear programming (LP) techniques. After sub-dividing the subjects according to their sex and physical activeness, a linear programming (LP) and Integer linear programming (ILP) technique was used to acquire the minimized cost for a 5-day dietary plan. It was observed that LP was able to obtain a lower cost compared to the ILP method and obtained different combinations of food. As a result, it was proven that college students can afford a well-balanced diet while sticking to their budget plan.
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