Chance-constrained programming is a relevant model for many concrete problems. However, it is known to be very hard to tackle directly. In this paper, the chance-constrained knapsack problem (CKP) is addressed. Relying on the recent advances in robust optimization, a tractable combinatorial algorithm is proposed to solve CKP. It always provides feasible solutions for CKP. Moreover, for two spec...

Capacitated location-allocation problem with stochastic demands is originally formulated as expected value model, chance-constrained programming and dependent-chance programming according to different criteria. For solving these stochastic models efficiently, the network simplex algorithm, stochastic simulation and genetic algorithm are integrated to produce a hybrid intelligent algorithm. Fina...

* Correspondence: [email protected] Department of Medical Education, Faculty of Medicine, 06490, Bahçelievler, Ankara, Turkey Full list of author information is available at the end of the article Abstract In this article, a method is developed to transform the chance-constrained programming problem into a deterministic problem. We have considered a chance-constrained programming problem u...

Resistance to autonomous systems comes in part from the perceived unreliability of the systems. Concerns can be addressed by guarantees of the probability of success. This is achieved in chanceconstrained constraint programming (CC-CP) by imposing constraints required for success, and providing upper-bounds on the probability of violating constraints. This extended abstract reports on novel unc...

Due to a wide variety of traffic requirements, the design, dimensioning and traffic management of Broadband Integrated Services Digital Networks (B-ISDN) involves the application of diverse methods and theories. In this paper we formulate a model which aims to combine results on the probabilistic analysis of congestion in the network with optimisation of traffic routing decisions. The optimizat...

The paper deals with two methods of solving optimization programs whereuncertainties occur: stochastic (in particular chance-constrained) programming androbust programming. We review briefly how these two methods deal with uncertaintyand what approximations are commonly used. Furthermore, we are concentrated onapproximations based on sample sets where some type of weak dependenc...

Project scheduling problem is to determine the schedule of allocating the loans to a project in order to balance the total cost and the completion time of the project under some constraints. This paper considers project scheduling problem in an uncertain environment, of which the duration time of each activity is an uncertain variable. Then uncertain chance-constrained programming model is cons...

The mixing set with a knapsack constraint arises in deterministic equivalent of chance-constrained programming problems with finite discrete distributions. We first consider the case that the chance-constrained program has equal probabilities for each scenario. We study the resulting mixing set with a cardinality constraint and propose facet-defining inequalities that subsume known explicit ine...