# Robust Discrete Optimization and Its Applications by Panos Kouvelis

By Panos Kouvelis

This ebook bargains with determination making in environments of important info un­ walk in the park, with specific emphasis on operations and construction administration purposes. For such environments, we propose using the robustness ap­ proach to selection making, which assumes insufficient wisdom of the choice maker in regards to the random kingdom of nature and develops a call that hedges opposed to the worst contingency that could come up. the most motivating components for a choice maker to take advantage of the robustness procedure are: • It doesn't forget about uncertainty and takes a proactive step in line with the truth that forecasted values of doubtful parameters won't happen in such a lot environments; • It applies to judgements of exact, non-repetitive nature, that are universal in lots of speedy and dynamically altering environments; • It money owed for the danger averse nature of choice makers; and • It acknowledges that even supposing determination environments are fraught with facts uncertainties, judgements are evaluated ex put up with the discovered information. For the entire above purposes, powerful judgements are pricey to the center of opera­ tional selection makers. This booklet takes an immense first step in offering determination help instruments and resolution tools for producing powerful judgements in various attention-grabbing software environments. powerful Discrete Optimization is a finished mathematical programming framework for powerful choice making.

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Additional info for Robust Discrete Optimization and Its Applications

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The international manufacturing manager usually faces an ex post evaluation of his/her international sourcing decisions over a rather short term period (in the range of a few months to less than two years) and with the use of cost data that reflects the actually realized (as compared to the planned or expected over the long run) macroeconomic data. , development of a supplier network that is relatively insensitive to the potential realizations of the macroeconomic parameters over the planning horizon, as a more appropriate approach for supplier selection in the volatile international environment.

The problem can be easily motivated within the context of planning multi-item orders in a limited storage space warehouse or retail facility. The facility orders n different items to meet forecasted demand over a planning horizon, with the main cost considerations involving economies of scale from ordering large quantities (as reflected in ordering costs per placed order) and inventory holding costs. Let us assume that the items are ordered in standardized containers that require a unit of storage space, and Di is the demand for item i in terms of the number of such containers.

M. , 501-511. 1 THE ROBUST DISCRETE OPTIMIZATION PROBLEM The main objective of this chapter is to discuss the formulation of an optimization problem the solution of which leads to the identification of robust decisions. In Chapter 1 we formally defined the Robustness Approach to Decision Making. According to our discussion, three different robustness criteria can be used for the selection of the robust decision. esF. esF. min max(J(X,D S) ses Relative Robustness: The relative robust decision XR is such that 26 P.