By Pawel Pawlewski, Allen Greenwood
The objective of this ebook is to offer qualitative elements of logistics operations and provide chain administration which support to enforce the sustainable coverage rules within the businesses and public sector’s associations. Authors in person chapters handle the problems concerning opposite community configuration, ahead and opposite offer chain integration, CO2 relief in transportation, development of the construction operations and administration of the restoration actions. a few top practices from varied international locations and industries are offered. This publication can be precious to either teachers and practitioners wishing to deepen their wisdom within the box of logistics operations and administration with reference to sustainability issues.
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Extra info for Process Simulation and Optimization in Sustainable Logistics and Manufacturing
Example text
Poeschel Verlag, Stuttgart Kisperska-Moron´ D (2000) Wpływ tendencji integracyjnych na rozwój zarza˛dzania logistycznego. Prace naukowe AE, Katowice Linstone HA, Turoff M (eds) (1975) The Delphi method: techniques and applications. Addison-Wesley Publishing Company, Reading 42 P. Cyplik et al. Löfgren K-G (1983) Produktion—teknik och ekonomi. LiberHermods, Malmö (in Swedish) Martino JP (1970) The precision of Delphi estimates. Technol Forecast 1(3):293–299 Pawlewski P (2014) Multimodal approach to modelling of manufacturing processes, variety management in manufacturing.
The second approach implies the validation and verification of the simulation system after the work on the model has been completed (Sargent 2001). Ł. Hadaś et al. 1 Production structure chart pertaining to the class of enterprises under analysis (Source own study) Table 2 Input data and the results of statistical analysis (Source own study) No. 1). 3 Three-dimensional space of validation experiments (Source own study) In order to analyses the results of simulation experiments a group of performance metrics was identified (see Table 2).
Hadaś et al. 46 Table 1 Classification of statistical measures (Source own study) Types of measures Level measures Dispersion measures Asymmetric measures Classical Absolute Arithmetic mean Geometric mean Absolute Variance Standard deviation Average deviation Absolute / direction/ Classical asymmetric measure Peakedness measures Absolute Peakedness measure Position Relative Classical coefficient of variance Relative/ direction and force/ Classical asymmetric measure Value range (−2; +2) Relative Peakedness coefficient Dominant Median Quartiles Absolute Scope Interquartile deviation Absolute/ direction/ Position asymmetric measure Relative Classical coefficient of variance Relative/ direction and force/ Position asymmetric measure Value range (−1; +1) sensitive measure of dispersion, yet it cannot be used as an absolute measure in the comparative analysis of dispersion in several populations or for several features in one population.