In this paper we consider a capacitated single allocation p-hub median problem (CSApHMP) which is to determine the location of p hubs, the allocation of non-hub nodes to hubs in the logistics network. This problem is formulated as an integer programming model with the objective of minimizing the sum of total transportation cost and fixed cost of the selected p hubs. Since the CSApHMP is NP-hard...

Traditional two-stage stochastic programming is risk-neutral; that is, it considers the expectation as the preference criterion while comparing the random variables (e.g., total cost) to identify the best decisions. However, in the presence of variability risk measures should be incorporated into decision making problems in order to model its effects. In this study, we consider a risk-averse tw...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DECOMPOSITION ALGORITHMS FOR TWO-STAGE STOCHASTIC INTEGER PROGRAMMING By John H. Penuel, Jr. August 2009 Chair: J. Cole Smith Major: Industrial and Systems Engineering Stochastic programming seeks to optimize decision making in uncertain...

Benders decomposition uses a strategy of “learning from one’s mistakes.” The aim of this paper is to extend this strategy to a much larger class of problems. The key is to generalize the linear programming dual used in the classical method to an “inference dual.” Solution of the inference dual takes the form of a logical deduction that yields Benders cuts. The dual is therefore very different f...

We study server scheduling in multiclass service systems under stochastic uncertainty in the customer arrival volumes. Common practice in such systems is to first identify staffing levels, and then determine schedules for the servers that cover these targets. We propose a new stochastic integer programming model that integrates these two decisions, which can yield lower scheduling costs by expl...

It is observed that the separated design of location for depots and routing for servicing customers often reach a suboptimal solution. So, solving location and routing problem simultaneously could achieve better results. In this paper, waste collection problem is considered with regard to economic and societal objective functions. A non-dominated sorting genetic algorithm (NSGA-II) is used to l...

This work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second st...

This work investigates the computational procedures used to obtain global solution to the Economic Linear Optimal Control (ELOC) problem. The proposed method employs the Generalized Benders Decomposition (GBD) algorithm. Compared to the previous branch and bound approach, a naive application GBD to the ELOC problem will improve computational performance, due to less frequent calls to computatio...

this paper proposes a new mathematical model for designing and planning postal parcels carriage and postal networks. the objective of postal network designing is to determine the location, size and connection between the postal stations in a city, province or country. in this paper, a kind of multiple locations-allocations hub problem with limited capacity in collecting, distributing and broadc...