Recoverable robust knapsacks: the discrete scenario case
نویسندگان
چکیده
Admission control problems have been studied extensively in the past. In a typical setting, resources like bandwidth have to be distributed to the different customers according to their demands maximizing the profit of the company. Yet, in real-world applications those demands are deviating and in order to satisfy their service requirements often a robust approach is chosen wasting benefits for the company. Our model overcomes this problem by allowing a limited recovery of a previously fixed assignment as soon as the data are known by violating at most k service promises and serving up to l new customers. Applying this approaches to the call admission problem on a single link of a telecommunication network leads to a recoverable robust version of the knapsack problem. In this paper, we show that for a fixed number of discrete scenarios this recoverable robust knapsack problem is weakly NP-complete and any such instance can be solved in pseudo-polynomial time by a dynamic program. If the number of discrete scenarios is part of the input, the problem is strongly NP-complete and in special cases not approximable in polynomial time, unless P = NP. Next to its complexity status we were interested in obtaining strong polyhedral descriptions for this problem. We thus generalized the well-known concept of covers to gain valid inequalities for the recoverable robust knapsack polytope. Besides the canonical extension of covers we introduce a second kind of extension exploiting the scenario-based problem structure and producing stronger valid inequalities. Furthermore, we present two extensive computational studies to (i) investigate the influence of parameters k and l to the objective and (ii) evaluate the effectiveness of our new class of valid inequalities. keywords: admission control, recoverable robustness, knapsack, extended cover inequalities
منابع مشابه
On Recoverable and Two-Stage Robust Selection Problems with Budgeted Uncertainty
In this paper the problem of selecting p out of n available items is discussed, such that their total cost is minimized. We assume that costs are not known exactly, but stem from a set of possible outcomes. Robust recoverable and two-stage models of this selection problem are analyzed. In the two-stage problem, up to p items is chosen in the first stage, and the solution is completed once the s...
متن کاملRecoverable Robust Knapsacks: Γ-Scenarios
In this paper, we investigate the recoverable robust knapsack problem, where the uncertainty of the item weights follows the approach of Bertsimas and Sim [3, 4]. In contrast to the robust approach, a limited recovery action is allowed, i.e., upto k items may be removed when the actual weights are known. This problem is motivated by the assignment of traffic nodes to antennas in wireless networ...
متن کاملStock Evaluation under Mixed Uncertainties Using Robust DEA Model
Data Envelopment Analysis (DEA) is one of the popular and applicable techniques for assessing and ranking the stocks or other financial assets. It should be noted that in the financial markets, most of the times, the inputs and outputs of DEA models are accompanied by uncertainty. Accordingly, in this paper, a novel Robust Data Envelopment Analysis (RDEA) model, which is capable to be used in t...
متن کاملRobust DEA under discrete uncertain data: a case study of Iranian electricity distribution companies
Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the real-world problems often deal with imprecise or ambiguous data. In this paper, we propose a novel robust data envelopment model (RDEA) to investigate the efficiencies of decision-making units (DMU) when there are discrete uncertain input and output data. The method is based ...
متن کاملA Robust Scenario Based Approach in an Uncertain Condition Applied to Location-Allocation Distribution Centers Problem
The paper discusses the location-allocation model for logistic networks and distribution centers through considering uncertain parameters. In real-world cases, demands and transshipment costs change over the period of the time. This may lead to large cost deviation in total cost. Scenario based robust optimization approaches are proposed where occurrence probability of each scenario is not know...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Optimization Letters
دوره 5 شماره
صفحات -
تاریخ انتشار 2011