An efficient preprocessing procedure for the multidimensional 0–1 knapsack problem
Discrete Applied Mathematics - Special volume: viewpoints on optimization
Solving a Real World Assignment Problem with a Metaheuristic
Journal of Heuristics
The Probabilistic Set-Covering Problem
Operations Research
Very Large-Scale Neighborhood Search for the K-Constraint Multiple Knapsack Problem
Journal of Heuristics
Mathematical Programming: Series A and B
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Active-constraint variable ordering for faster feasibility of mixed integer linear programs
Mathematical Programming: Series A and B
A Sample Approximation Approach for Optimization with Probabilistic Constraints
SIAM Journal on Optimization
Evaluating project completion time in project networks with discrete random activity durations
Computers and Operations Research
MIP reformulations of the probabilistic set covering problem
Mathematical Programming: Series A and B
An integer programming approach for linear programs with probabilistic constraints
Mathematical Programming: Series A and B
Integer optimization by local search: a domain-independent approach
Integer optimization by local search: a domain-independent approach
The Multidimensional Knapsack Problem: Structure and Algorithms
INFORMS Journal on Computing
Scalable Heuristics for a Class of Chance-Constrained Stochastic Programs
INFORMS Journal on Computing
A heuristic approach for resource constrained project scheduling with uncertain activity durations
Computers and Operations Research
IPCO'10 Proceedings of the 14th international conference on Integer Programming and Combinatorial Optimization
On mixing sets arising in chance-constrained programming
Mathematical Programming: Series A and B
Capital rationing problems under uncertainty and risk
Computational Optimization and Applications
Uniform quasi-concavity in probabilistic constrained stochastic programming
Operations Research Letters
A robust approach to the chance-constrained knapsack problem
Operations Research Letters
Relaxations for probabilistically constrained programs with discrete random variables
Operations Research Letters
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Integer problems under joint probabilistic constraints with random coefficients in both sides of the constraints are extremely hard from a computational standpoint since two different sources of complexity are merged. The first one is related to the challenging presence of probabilistic constraints which assure the satisfaction of the stochastic constraints with a given probability, whereas the second one is due to the integer nature of the decision variables. In this paper we present a tailored heuristic approach based on alternating phases of exploration and feasibility repairing which we call Express (Explore and Repair Stochastic Solution) heuristic. The exploration is carried out by the iterative solution of simplified reduced integer problems in which probabilistic constraints are discarded and deterministic additional constraints are adjoined. Feasibility is restored through a penalty approach. Computational results, collected on a probabilistically constrained version of the classical 0---1 multiknapsack problem, show that the proposed heuristic is able to determine good quality solutions in a limited amount of time.