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exchange that is addressable via mapping from the enterprise to the universal translator and from there to diverse users Any enterprise that desires to participate in the community is responsible for exchanging data through the agreed upon utility 19 Outgoing data may or may not satisfy user needs Data that is processed through the enterprise utility solution that is a product of smart data strategy will satisfy end-user needs Data is overly redundant Data redundancy excesses are eliminated through this strategy Data is overly costly Smart data strategy aims at providing the most costeffective means for enterprise participants to exchange data It also contributes to overall reduction in operations and maintenance costs Data is not actionable Data is not actionable if its source is unaccredited or unknown Processing data through an enterprise with smart data strategy provides data that is actionable When de cient for whatever reasons, the caveats are identi ed and attributed to the source or cause 20 Decision support is de cient because needed data is absent, incomplete, and lacking in quality The best way to ensure that decisions are supported with adequate data is to identify decision requirements as part of the smart data strategy 21 Sense making and prediction are de cient for the same reasons, and so is data for planning and problem solving Requirements for sense making and prediction must be anticipated When they are not, the smart data system will support ad hoc queries with reliable data and with known caveats 22 Data storage, access, and processing are excessively expensive, or the enterprise does not have a good metric for knowing whether data management is effective and ef cient or not Smart data strategy advocates an audit that will produce a baseline from which to improve performance 23 Infrastructure costs cannibalize resources, leaving little for improvement and discretion needed for agile and adaptive performance Having the discipline to halt the cause of de cient performance is made easier by having a detailed plan to mitigate risk from change and improvement 24 Enterprise performance is affected by incoming data Data from Customers Data from customers identi es and describes them, including demographic and psychographic data Customer pro les can be detailed and private Customers may place restrictions on using their data Some customer classi cations include retail and wholesale, for instance In the Department of Defense, the lines between retail and wholesale are blurring as a result of seeing cost reductions and performance gains similar to those discovered by WalMart, for instance Also, the lines are blurring between logistics and transportation.

Bian et al [66], and Sierra and Echeverr [788] independently proposed that the ia components of genotype be transformed to polar coordinates Instead of the original genotype, the polar genotypes are evolved For an nx -dimensional Cartesian coordinate, the corresponding polar coordinate is given as (1237) (r, nx 2 , , 1 , ) where 0 < 2 , 0 q for q = 1, , nx 2, and r > 0 Each individual is therefore represented as (1238) i (t) = (xp (t), i (t)) i where , xp = (r, nx 2, , 1 , ) Polar coordinates are transformed back to Cartei sian coordinates as follows: x1 x2 x3 xi xn = = = = = = = r cos sin 1 sin 2 sin nx 2 r sin sin 1 sin 2 sin nx 2 r cos 1 sin 2 sin nx 2 (1239) r cos i 2 sin i 1 sin nx 2

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In total, the company has 54 employees However, if we assume that the parttime staff all work half time, then the eight part-time positions can be reduced to four FTEs, which decreases the total headcount to 50 personnel Another issue is what constitutes direct labor personnel the company has a group of clearly defined direct labor personnel, as well as a materials handling support staff and two production supervisors The company can use any combination of these groups for its sales per direct labor measurement, as long as it consistently applies the measurement over time However, the technically correct approach is to include in the measure any positions that are required for the proper completion of production efforts, which would require the inclusion of all three categories of labor If this approach were not used, the person doing the measuring might be tempted to artificially inflate the measurement results by shifting direct labor personnel into other labor categories that fall just outside the definition The result of these measurements is overall sales per employee of $84,000 ($4,200,000 in revenues, divided by 50 employees) and sales per direct labor employee of $135,484 ($4,200,000 in revenues, divided by 31 employees) The 31 employee figure is derived by adding 22 direct labor personnel to the three FTEs represented by the six part-time direct labor personnel, plus the production supervisors and material handling staff This formula is subject to a high degree of variation, depending upon how personnel are counted For example, shifting away from employees to an outsourced solution or to the in-house use of temporary employees can artificially reduce the number of FTEs, as can the use of overtime by a smaller number of employees Also, comparing the number of FTEs to revenue has a less direct bearing on profitability than comparing revenues to the total of all salaries and wages expenses; for example, one company with a large headcount but low pay per person may be more profitable than a company having a lesser headcount but a much higher salary per person Also, some capital-intensive industries have so few employees in relation to the sales volume generated that this measure has much less significance than other measures, such as sales to fixed assets.

The mutation operator uses deviations to adjust the and q angles: = ( l (t) + ,l (t)N (0, 1)) mod 2 lq (t) + (t)Nq (0, 1)) mod lq (t) = ( lq l (1240) (1241)

125 Evolution Strategy Variants Algorithm 122 Polar Evolution Strategy Set the generation counter, t = 0; Initialize the strategy parameters, , ,q , q = 1, , nx 2; Create and initialize the population, C(0), as follows:; for i = 1, , do r = 1; i (0) U (0, 2 ); iq (0) U (0, ), q = 1, , nx 2; xp (0) = (r, i (0), i (0)); i i (0) = (xp (0), i (0)); i end for each individual, l (0) C(0) do Transform polar coordinate xp (0) to Cartesian coordinate nxi (0); i Evaluate the tness, f (xi (0)); end while stopping condition(s) not true do for l = 1, , , generate offspring do Randomly choose two parents; Create o spring, l (t), using local, discrete recombination; Mutate l (t) to produce l (t); Transform xp (t) back to Cartesian xl (t); l Evaluate the tness, f (xi (t)); end Select individuals from the o spring to form C(t + 1); t = t + 1; end

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