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Based on the above discussion, this study aims at formulating profit maximization inventory model for deteriorating items with stochastic price sensitive demand and promotional efforts.
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We formulate this profit optimization problem and derive the optimum price solution.
The model is formulated as profit maximization problem with respect to the retailer and solved with the help of genetic algorithm (GA) and PSO.
This model is formulated as profit maximization problem with respect to the retailer and solved by two metaheuristics, which are the genetic algorithm and the particle-swarm optimization.
The model is formulated as a profit maximization problem and solved using Genetic Algorithm.
The objective of each aggregator is to maximize its profit, as formulated in (6).
The franchisor total profit is formulated as: mathrm{P}left tau, X,Aright)={displaystyle {sum}_{t=1}^{tau}delta {X}_t+{displaystyle {sum}_{t=tau +1}^ T{X}_tleft 1-cright -{A}_t T{X}_tleft 1-cright -{A}_t T{X}_tleft 1-cright -{A}_t
We formulate a store's profit as a jointly concave function in demand and investment, and show that the corresponding ROI function is unimodal.
The overall bottom-up problem is formulated as a stochastic profit maximization model for the DR aggregator, in which the risk is taken into account using the Conditional Value-at-Risk (CVaR) measure.
In order to evaluate the advantages and disadvantages of the design alternatives, the incremental objective function between batch and fed-batch, batch and different operations in a membrane bioreactor was formulated in terms of profit maximization.
Specifically, we formulate a transcoding time constrained profit function to evaluate the profit from caching each version of an object.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com