9 research outputs found
A decomposition approach to a stochastic model for supply-and-return network design
This paper presents a generic stochastic model for the design of networks comprising
both supply and return channels, organized in a closed loop system. Such situations
are typical for manufacturing/re-manufacturing type of systems in reverse logistics.
The model accounts for a number of alternative scenarios, which may be constructed
based on critical levels of design parameters such as demand or returns. We propose
a decomposition approach for this model based on the branch and cut procedure known as
the integer L-shaped method. Computational results show a consistent performance
efficiency of the method for the addressed location problem. The stochastic solutions
obtained in a numerical setting generate a significant improvement in terms of average
performance over the individual scenario solutions. A solution methodology as presented
here can contribute to overcoming notorious challenges of stochastic network design models,
such as increased problem sizes and computational difficulty
Simulation-based solution of stochastic mathematical programs with complementarity constraints: sample-path analyis
We consider a class of stochastic mathematical programs with
complementarity constraints, in which both the objective and the
constraints involve limit functions or expectations that need to be
estimated or approximated. Such programs can be used for modeling
"average" or steady-state behavior of complex stochastic
systems. Recently, simulation-based methods have been successfully
used for solving challenging stochastic optimization problems and
equilibrium models. Here we broaden the applicability of so-called
the sample-path method to include the solution of certain stochastic
mathematical programs with equilibrium constraints. The convergence
analysis of sample-path methods rely heavily on stability
conditions. We first review necessary sensitivity results, then
describe the method, and provide sufficient conditions for its
almost-sure convergence. Alongside we provide a complementary
sensitivity result for the corresponding deterministic problems. In
addition, we also provide a unifying discussion on alternative set of
sufficient conditions, derive a complementary result regarding the
analysis of stochastic variational inequalities, and prove the
equivalence of two different regularity conditions
A scenario aggregation based approach for determining a robust airline fleet composition
Strategic airline fleet planning is one of the major issues addressed
through newly initiated decision support systems, designed to assist
airlines and aircraft manufacturers in assessing the benefits of the
emerging concept of dynamic capacity allocation. We present background
research connected with such a system, which aims to explicitly account
for the stochastic nature of passenger demand in supporting decisions
related to the fleet composition problem. We address this problem through
a scenario aggregation based approach and present results on representative
case studies based on realistic data. Our investigations establish clear
benefits of a stochastic approach as compared with deterministic formulations,
as well as its implementation feasibility using state-of-the-art
optimization software
Stochastic approaches for product recovery network design: a case study
Increased uncertainty is one of the characteristics of product recovery networks. In particular the strategic design of their logistic infrastructure has to take uncertain information into account. In this paper we present stochastic programming based approaches by which a deterministic location model for product recovery
network design may be extended to explicitly account for the uncertainties. Such a stochastic model seeks a solution which is appropriately balanced between some alternative scenarios identified by field experts. We apply the stochastic models to a representative real case study on recycling sand from demolition waste in
The Netherlands. The interpretation of the results is meant to give more insight into decision-making for reverse logistics
A Scenario Aggregation Based Approach for Determining a Robust Airline Fleet Composition
Strategic airline fleet planning is one of the major issues addressed through newly initiated decision support systems, designed to assist airlines and aircraft manufacturers in assessing the benefits of the emerging concept of dynamic capacity allocation. We presen