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Optimality modeling is the modeling aspect of optimization theory. It allows for the calculation and visualization of the costs and benefits that influence the outcome of a decision, and contributes to an understanding of adaptations. The approach based on optimality models in biology is sometimes called optimality theory. [1]
Price optimization utilizes data analysis to predict the behavior of potential buyers to different prices of a product or service. Depending on the type of methodology being implemented, the analysis may leverage survey data (e.g. such as in a conjoint pricing analysis [7]) or raw data (e.g. such as in a behavioral analysis leveraging 'big data' [8] [9]).
Typically, supply-chain managers aim to maximize the profitable operation of their manufacturing and distribution supply chain. This could include measures like maximizing gross margin return on inventory invested (balancing the cost of inventory at all points in the supply chain with availability to the customer), minimizing total operating expenses (transportation, inventory and ...
When drawing diagrams for businesses, allocative efficiency is satisfied if output is produced at the point where marginal cost is equal to average revenue. This is the case for the long-run equilibrium of perfect competition. Productive efficiency occurs when units of goods are being supplied at the lowest possible average total cost.
Cost function. In economics, the cost curve, expressing production costs in terms of the amount produced. In mathematical optimization, ...
Half cost strategies: ambitious strategies which aim to reduce the costs of specific production processes or value adding stages to 1/N of the previous cost. [7] Examples specifically focussed on the use of suppliers and the costs of goods and services supplied include: Supplier consolidation: see examples in the aerospace manufacturing industry
In linear programming, reduced cost, or opportunity cost, is the amount by which an objective function coefficient would have to improve (so increase for maximization problem, decrease for minimization problem) before it would be possible for a corresponding variable to assume a positive value in the optimal solution.
For example, a soda bottle can have different packaging variations, flavors, nutritional values. It is possible to optimize a product by making minor adjustments. Typically, the goal is to make the product more desirable and to increase marketing metrics such as Purchase Intent, Believability, Frequency of Purchase, etc.