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Price uncertainty

R6 - Price uncertainty consideration in planning Spot demand quantity and prices are uncertain in commodity business specifically in the considered planning horizon of 3-12 months. Since price is the main buying criterion in commodity business, mid-term demand quantity is mainly influenced by the price level. If spot demand quantity and prices depend on each other, uncertainty can be limited to one parameter while the other parameter is kept constant. The spot demand price is considered as uncertain in this problem leading to different turnover scenarios for the same sales quantity. Lababidi et al. (2004) presenting a petrochemical case that had to consider uncertainty in market prices and raw material costs in supply chain optimization. [Pg.114]

Lababidi et al. (2004) incorporate uncertainty and stochastic market prices and raw material costs for a petrochemical case. They modeled market price and raw material price uncertainty as given and analyzed the effects on production utilization. They initially observed that prices can have significant influence on production plans and utilization. [Pg.129]

Up to this point, it is assumed that prices are deterministic, which is true for contract demand and procurement but is not necessarily true for spot demand and procurement prices. Therefore, an important value chain planning requirement is the consideration of uncertain prices and price scenarios. Now, uncertain spot demand prices are under consideration and it is illustrated how price uncertainty can be integrated into the model in order to reach robust planning solutions. [Pg.243]

In the considered value chain planning problem, the uncertainty of spot sales prices impacts the profitability of the overall value chain plan, since volume decisions can lead to profit-suboptimal plans, if the average sales price cannot be realized as planned. Therefore, price volatility is considered as an external (stochastic) influence in the considered value chain planning problem. The following model extensions account for this uncertainty and try to derive methods to achieve more robust plans with respect to profit results with contributions from Habla (2006). The objective of the proposed modeling approach is to maximize profit for the entire value chain network. It is assumed that the company behaves risk-averse in face of the price uncertainty. [Pg.244]

The objective of the proposed modeling approach is to maximize profit for the entire value chain network. Two optimization strategies can be applied incorporating spot sales price scenarios to reflect price uncertainty ... [Pg.246]

This approach is proposed by Chen/Lee (2004) to reach more robust solutions considering probabilistic for in this case demand quantity scenarios without considering price uncertainty. [Pg.247]

Uncertainty in market demand introduces randomness in constraints for production requirements of intermediates and saleable products, as given by Equation (6.4). The sampling methodology employed for scenario construction is similar to the case of price uncertainty in Approach 1, involving the generation of representative scenarios of demand uncertainty for N number of products with the associated probabilities that indicate their comparative frequency of occurrence. [Pg.117]

A 5% standard deviation from the mean value of market demand for the saleable products in the LP model is assumed to be reasonable based on statistical analyses of the available historical data. To be consistent, the three scenarios assumed for price uncertainty with their corresponding probabilities are similarly applied to describe uncertainty in the product demands, as shown in Table 6.2, alongside the corresponding penalty costs incurred due to the unit production shortfalls or surpluses for these products. To ensure that the original information structure associated with the decision process sequence is respected, three new constraints to model the scenarios generated are added to the stochastic model. Altogether, this adds up to 3 x 5 = 15 new constraints in place of the five constraints in the deterministic model. [Pg.125]

Uncertainty in future allowance prices leads to delay in investment decisions. By waiting, a company gains more knowledge about future C02 prices, and thereby makes better decisions. Furthermore, in the presence of price uncertainty, risk aversion is also likely to reduce investment.40 The risk of low C02 prices, or even a price crash due to allocations based on high emission forecasts, represents a significant hurdle for investment in low-carbon investments. Obviously, companies are prepared to bear risks, but they generally prefer to take risks in their core business, where this can create strategic opportunities.41... [Pg.150]

Private-sector benefits Provide more-secure and higher-quality electricity Become more profitable Help companies meet environmental and other regulations Reduce electricity costs—in particular, demand charges Reduce price uncertainty Increase safety Back-up generators... [Pg.56]

For the key chemical products which must support the economics of a petrochemical refinery pricing uncertainties appear inevitable. However, as long as chemical feedstock demands in the U.S. continue to grow more rapidly than fuels and as long as chemical companies remain uneasy over their growing reliance on refiners, the petrochemical refinery concept will receive active attention from chemical companies. [Pg.143]

Hodder, J.E. and Jucker, J.V. (1985a) A simple plant-location model for quantity setting firms subject to price uncertainty. European Journal of Operational Research, 21, 39-46. [Pg.708]

Cheali PA, Quaglia KV, Gernaey GS. Effect of market price uncertainties on the design of optimal biorefmery systems—a systematic approach. Ind Eng Chem Res 2014 53 6021-32. [Pg.378]

The real world problem is much more complex for several reasons customers purchasing from other competing manufacturers, a large number of customers with uncertain buying habits, raw material price uncertainty, and the uncertain manufacturing lead times. Therefore, the challenge each partner faces is to maximize its share of value, while increasing the total supply chain value. [Pg.29]


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See also in sourсe #XX -- [ Pg.124 ]

See also in sourсe #XX -- [ Pg.124 ]




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Robust Planning with Price Uncertainties

Uncertainty prices/market demands/product

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