Multi-component Maintenance Optimization: A Stochastic Programming Approach

Maintenance optimization has been extensively studied in the past decades. However, most of the existing maintenance models focus on single-component systems. Multi-component maintenance optimization, which joins the stochastic failure processes with the combinatorial maintenance grouping problems, remains as an open issue. To address this challenge, we study this problem in a finite planning horizon by … Read more

On tradeoffs between treatment time and plan quality of volumetric-modulated arc therapy with sliding-window delivery

The purpose of this study is to give an exact formulation of optimization of volumetric-modulated arc therapy (VMAT) with sliding-window delivery, and to investigate the plan quality effects of decreasing the number of sliding-window sweeps made on the 360-degree arc for a faster VMAT treatment. In light of the exact formulation, we interpret an algorithm … Read more

Heuristic Methods for The Capacitated Stochastic Lot-Sizing Problem Under The Static-Dynamic Uncertainty Strategy

We consider a lot-sizing problem in a single-item single-stage production system facing non-stationary stochastic demand in a nite planning horizon. Motivated by practice, the set-up times need to be deter- mined and frozen once and for all at the beginning of the horizon while decisions on the exact lot sizes can be deferred until the … Read more

Efficient heuristic algorithm for identifying critical nodes in planar networks

This paper presents a new method for identifying critical nodes in planar networks. We propose an efficient method to evaluate the quality of solutions by using special properties of planar networks. It enables us to develop a computationally efficient heuristic algorithm for the problem. The proposed algorithm assisted on randomly generated planar networks. The experimental … Read more

MSEA.jl: A Multi-Stage Exact Algorithm for Bi-objective Pure Integer Linear Programming in Julia

We present a new exact method for bi-objective pure integer linear programming, the so-called Multi-Stage Exact Algorithm (MSEA). The method combines several existing exact and approximate algorithms in the literature to compute the entire nondominated frontier of any bi-objective pure integer linear program. Each algorithm available in MSEA has multiple versions in the literature. Hence, … Read more

The first heuristic specifically for mixed-integer second-order cone optimization

Mixed-integer second-order cone optimization (MISOCO) has become very popular in the last decade. Various aspects of solving these problems in Branch and Conic Cut (BCC) algorithms have been studied in the literature. This study aims to fill a gap and provide a novel way to find feasible solutions early in the BCC algorithm. Such solutions … Read more

Probabilistic Variational Formulation of Binary Programming

A probabilistic framework for large classes of binary integer programming problems is constructed. The approach is given by a mean field annealing scheme where the annealing phase is substituted by the solution of a dual problem that gives a lower (upper) bound for the original minimization (maximization) integer task. This bound has an information theoretic … Read more

Robust Optimization for the Vehicle Routing Problem with Multiple Deliverymen

This paper studies the vehicle routing problem with time windows and multiple deliverymen in which customer demands are uncertain and belong to a predetermined polytope. In addition to the routing decisions, this problem aims to define the number of deliverymen used to provide the service to the customers on each route. A new mathematical formulation … Read more

Polynomial-Time Methods to Solve Unimodular Quadratic Programs With Performance Guarantees

We develop polynomial-time heuristic methods to solve unimodular quadratic programs (UQPs) approximately, which are known to be NP-hard. In the UQP framework, we maximize a quadratic function of a vector of complex variables with unit modulus. Several problems in active sensing and wireless communication applications boil down to UQP. With this motivation, we present three … Read more

Locality sensitive heuristics for solving the Data Mule Routing Problem

A usual way to collect data in a Wireless Sensor Network (WSN) is by the support of a special agent, called data mule, that moves between sensor nodes and performs all communication between them. In this work, the focus is on the construction of the route that the data mule must follow to serve all … Read more