Lower Bounding Procedures for the Single Allocation Hub Location Problem

This paper proposes a new lower bounding procedure for the Uncapacitated Single Allocation p-Hub Median Problem based on Lagrangean relaxation. For solving the resulting Lagrangean subproblem, the given problem structure is exploited: it can be decomposed into smaller subproblems that can be solved efficiently by combinatorial algorithms. Our computational experiments for some benchmark instances demonstrate … Read more

Approximate Uni-directional Benders Decomposition

We examine a decomposition approach to find good quality feasible solutions. In particular, we study a method to reduce the search-space by decomposing a problem into two partitions, where the second partition (i.e., the subproblem) contains the fixed solution of the first (i.e., the master). This type of approach is usually motivated by the presence … Read more

Scheduling with Fixed Maintenance, Shared Resources and Nonlinear Feedrate Constraints: a Mine Planning Case Study

Given a short term mining plan, the task for an operational mine planner is to determine how the equipment in the mine should be used each day. That is, how crushers, loaders and trucks should be used to realise the short term plan. It is important to achieve both grade targets (by blending) and maximise … Read more

An MILP approach to Multi-location, Multi-Period Equipment Selection for Surface Mining with Case Studies

In the surface mining industry, the Equipment Selection Problem involves choosing an appropriate fleet of trucks and loaders such that the long-term mine plan can be satisfied. An important characteristic for multi-location (multi-location and multi-dumpsite) mines is that the underlying problem is a multi-commodity flow problem. The problem is therefore at least as difficult as … Read more

On globally solving the maximum weighted clique problem

In this paper, we consider a combinatorial optimization problem, the Maximum Weighted Clique Problem (MWCP), a NP-hard problem. The considered problem is first formulated in the form of binary constrained quadratic program and then reformulated as a Difference Convex (DC) program. A global optimal solution is found by applying DC Algorithm (DCA) in combining with … Read more

A Compact Linearisation of Euclidean Single Allocation Hub Location Problems

Hub location problems are strategic network planning problems. They formalise the challenge of mutually exchanging shipments between a large set of depots. The aim is to choose a set of hubs (out of a given set of possible hubs) and connect every depot to a hub so that the total transport costs for exchanging shipments … Read more

On the Coherent Risk Measure Representations in the Discrete Probability Spaces

We give a complete characterization of both comonotone and not comonotone coherent risk measures in the discrete finite probability space, where each outcome is equally likely. To the best of our knowledge, this is the first work that characterizes and distinguishes comonotone and not comonotone coherent risk measures via a simplified AVaR representation in this … Read more

The Value of Flexibility in Robust Location-Transportation Problems

This article studies a multi-period capacitated fixed-charge location-transportation problem in which, while the location and capacity of each facility need to be determined immediately, the determination of final production and distribution of products can be delayed until actual orders are received in each period. In contexts where little is known about future demand, robust optimization, … Read more

Sample approximations of multiobjective stochastic optimization problems

The article describes approximation technique for solving multiobjective stochastic optimization problems. As a generalized model of a stochastic system to be optimized a vector “input — random output” system is used. Random outputs are converted into a vector of deterministic performance/risk indicators. The problem is to find those inputs that correspond to Pareto-optimal values of … Read more

Parameter-free Sampled Fictitious Play for Solving Deterministic Dynamic Programming Problems

To facilitate fast solution of deterministic dynamic programming problems, we present a parameter-free variation of the Sampled Fictitious Play (SFP) algorithm. Its random tie-braking procedure imparts a natural randomness to the algorithm which prevents it from “getting stuck” at a local optimal solution and allows the discovery of an optimal path in a finite number … Read more