scholarly journals Step-Wise Group Screening Designs with Unequal A-Priori Probabilities and Errors in Observations

2003 ◽  
Vol 8 (2) ◽  
pp. 153
Author(s):  
M.M. Manene
Keyword(s):  
Cost Function ◽  
Group Size ◽  
A Priori ◽  
Expected Number ◽  
Total Cost ◽  
Screening Designs ◽  
Expected Total Cost

The performance of step-wise group screening with unequal a-priori probabilities in terms of the expected number of runs and the expected maximum number of incorrect decisions is considered. A method of obtaining optimal step-wise designs with unequal a-priori probabilities is presented for the case in which the direction of each defective factor is assumed to be known a -priori and observations are subject to error. An appropriate cost function is introduced and the value of the group size which minimizes the expected total cost is obtained.  

Sustainable optimal ordering quantity for non-instantaneous deteriorating items under joint replenishment with substitution and carbon emission

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ranu Singh ◽  
Vinod Kumar Mishra
Keyword(s):  
Cost Function ◽  
Carbon Emission ◽  
Inventory Model ◽  
Deteriorating Items ◽  
Joint Replenishment ◽  
Content Type ◽  
Total Cost ◽  
Optimal Ordering ◽  
Ordering Quantity ◽  
Total Cost Function

Purpose Carbon emission is a significant issue for the current business market and global warming. Nowadays, most countries have focused to reduce the environmental impact of business with durable financial benefits. The purpose of this study is to optimize the entire cost functions with carbon emission and to find the sustainable optimal ordering quantity for retailers. Design/methodology/approach This paper illustrates a sustainable inventory model having a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. In this model demand and deterioration rate are considered as deterministic, constant and triangular fuzzy numbers. The objective is to find the optimal ordering quantity for retailers and to minimize the total cost function per unit time with carbon emission. The model is then solved with the help of Maple software. Findings This paper presents a solution method and also develop an algorithm to determine the order quantities which optimize the total cost function. A numerical experiment illustrates the improvement in optimal total cost of the inventory model with substitution over without substitution. The graphical results show the convexity of the cost function. Finally, sensitivity analysis is given to get the impact of parameters and validity of the model. Originality/value This study considers a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. From the literature review, in the authors’ knowledge no researcher has undergone this kind of study.

scholarly journals On Time-Frequency Synchronization in LoRa System: From Analysis to Near-Optimal Algorithm

2021 ◽  
Author(s):  
Vincent Savaux ◽  
Christophe Delacourt ◽  
Patrick Savelli
Keyword(s):  
Cost Function ◽  
Optimal Algorithm ◽  
A Priori ◽  
Low Complexity ◽  
Frequency Offset ◽  
Maximization Problem ◽  
Frequency Synchronization ◽  
Time Frequency ◽  
Time Offset ◽  
Ml Estimator

This paper deals with time and frequency synchronization in LoRa system based on the preamble symbols. A thorough analysis of the maximum likelihood (ML) estimator of the delay (time offset) and the frequency offset shows that the resulting cost function is not concave. As a consequence the a priori solution to the maximization problem consists in exhaustively searching over all the possible values of both the delay and the frequency offset. Furthermore, it is shown that these parameters are intertwined and therefore they must be jointly estimated, leading to an extremely complex solution. Alternatively, we show that it is possible to recover the concavity of the cost function, from which we suggest a low-complexity synchronization algorithm, whose steps are described in detail. Simulations results show that the suggested method reaches the same performance as the ML exhaustive search, while the complexity is drastically reduced, allowing for a real-time implementation of a LoRa receiver. <br>

Optimization of Leased Equipment Maintenance Policy Based on History Failure Data

2021 ◽  
pp. 2150030
Author(s):  
Ke Dong ◽  
Kehong Chen
Keyword(s):  
Power Law ◽  
Cost Model ◽  
Maintenance Strategy ◽  
Maintenance Policy ◽  
Power Law Process ◽  
Total Cost ◽  
Cost Rate ◽  
Failure Data ◽  
Expected Total Cost ◽  
The Cost

We propose a maintenance policy for new equipment on a repair-refund maintenance strategy in this paper and derive the optimal lease period from the lessor’s perspective based on independent and identical distribution of historical failure data which obey power law process. The cost model of a full refund and a proportional refund is studied, and the corresponding optimal leasing period is determined by reducing the expected total cost rate to the largest extent. We use a numerical example to illustrate the proposed cost model and analyze the sensitivity of related parameters. Furthermore, we show that the proportional refund policy is preferable than a full refund to the lessor. Finally, according to the simulation outcome, the proposed methods are effective and instructions for lessor in regard to equipment lease are provided.

AN MLP TRAINING ALGORITHM TAKING INTO ACCOUNT KNOWN ERRORS ON INPUTS AND OUTPUTS

2002 ◽  
Vol 12 (05) ◽  
pp. 369-379
Author(s):  
J. SVENSSON
Keyword(s):  
Cost Function ◽  
A Priori ◽  
Hessian Matrix ◽  
Predictive Distribution ◽  
Training Algorithm ◽  
Posterior Predictive Distribution ◽  
Network Function ◽  
Error Bars ◽  
Mlp Network ◽  
Inputs And Outputs

A training algorithm is introduced that takes into account a priori known errors on both inputs and outputs in an MLP network. The new cost function introduced for this case is based on a linear approximation of the network function over the input distribution for a given input pattern. Update formulas, in the form of the gradient of the new cost function, is given for a MLP network, together with expressions for the Hessian matrix. This is later used to calculate error bars in a Bayesian framework. The error bars thus derived are discussed in relation to the more commonly used width of the target posterior predictive distribution. It will also be shown that the taking into account of known input uncertainties in the way suggested in this article will have a strong regularizing effect on the solution.

OPTIMAL DESIGN OF BINARY WEIGHTED k-OUT-OF-n SYSTEMS

2008 ◽  
Vol 15 (05) ◽  
pp. 425-440 ◽  
Author(s):  
WEI LI ◽  
MING J. ZUO ◽  
YI DING
Keyword(s):  
Optimal Design ◽  
System Reliability ◽  
System Size ◽  
Optimization Models ◽  
Total System ◽  
Total Cost ◽  
Total Utility ◽  
Need To Evaluate ◽  
Expected Total Cost ◽  
Binary Weighted

In this paper, we consider the optimal design of the binary weighted k-out-of-n system. The binary weighted k-out-of-n: G system works if and only if the total utility of all working components is at least k. In the design process, we need to evaluate system reliability repetitively. The universal generating function (UGF) approach is used for this purpose when the system size is small or moderate. When the size of the system is large, the recursive approach is used, which is more efficient. Two optimal models are formulated. One is to minimize the expected total cost while guaranteeing the system reliability higher than a pre-specified value; the other is to maximize the system reliability with the constraints on total system cost. Genetic algorithms (GA) and Tabu Search (TS) methods are both used to solve the proposed optimization models. Since the key to a good TS algorithm is usually quite problem-specific policies and memory structures, there is no existing general TS tool available. Therefore more details of the TS approach used in this paper are discussed than the GA approach. The results obtained with these two methods are compared. The results illustrate that both methods are powerful tools for solving these kinds of problems. However TS is more efficient than GA in computation. The materials in this paper have been published in 19.

A Monotonicity Result for Inspecting Independent Items

1989 ◽  
Vol 3 (1) ◽  
pp. 135-140
Author(s):  
F.K. Hwang ◽  
S.G. Papastavridis
Keyword(s):  
Cost Function ◽  
Failure Probability ◽  
General Model ◽  
Group Testing ◽  
Probabilistic Algorithms ◽  
Expected Number ◽  
Monotonicity Result ◽  
Crucial Part

Recently, the conjecture that the expected number of tests is nondecreasing in the failure probability for binomial group testing has been proved. The proof has also been extended to three models of multiaccess systems. However, probabilistic algorithms are used as a crucial part of these proofs. In this paper, we give conceptually simpler new proofs without using probabilistic algorithms. We also extend the result to a more general model where the number of tests is replaced by a cost function.

Multi-product total cost function for higher education: a case of bible colleges

2001 ◽  
Vol 20 (3) ◽  
pp. 297-303 ◽  
Author(s):  
Rajindar K. Koshal ◽  
Manjulika Koshal ◽  
Ashok Gupta
Keyword(s):  
Higher Education ◽  
Cost Function ◽  
Bible Colleges ◽  
Total Cost ◽  
Total Cost Function

scholarly journals The constrained gravity model with power function as a cost function

2006 ◽  
Vol 2006 ◽  
pp. 1-13
Author(s):  
Bablu Samanta ◽  
Sanat Kumar Mazumder
Keyword(s):  
Cost Function ◽  
Gravity Model ◽  
Power Function ◽  
Transportation Problem ◽  
Trip Distribution ◽  
Total Cost ◽  
Numerical Example ◽  
Particular Solution ◽  
Generalized Cost ◽  
The Given

A gravity model for trip distribution describes the number of trips between two zones, as a product of three factors, one of the factors is separation or deterrence factor. The deterrence factor is usually a decreasing function of the generalized cost of traveling between the zones, where generalized cost is usually some combination of the travel, the distance traveled, and the actual monetary costs. If the deterrence factor is of the power form and if the total number of origins and destination in each zone is known, then the resulting trip matrix depends solely on parameter, which is generally estimated from data. In this paper, it is shown that as parameter tends to infinity, the trip matrix tends to a limit in which the total cost of trips is the least possible allowed by the given origin and destination totals. If the transportation problem has many cost-minimizing solutions, then it is shown that the limit is one particular solution in which each nonzero flow from an origin to a destination is a product of two strictly positive factors, one associated with the origin and other with the destination. A numerical example is given to illustrate the problem.

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