Decentralised Shared Resource Constraint Scheduling with Confidentiality Protection

As resources become scarce and expensive, it has become increasingly important for players in a decentralised supply chain to collaborate. One of the main challenges in collaboration is to find close to globally optimal solutions without sharing individual player’s private data. Taking a decentralised resource constrained scheduling problem as an example we present a methodology … Read more

Public Facility Location Using Dispersion, Population, and Equity Criteria

Administrators/Decision Makers (DMs) responsible for making locational decisions for public facilities have many other overriding factors to consider that dominate traditional OR/MS objectives that relate to response time. We propose that an appropriate role for the OR/MS analyst is to help the DMs identify a good set of solutions rather than an optimal solution that … Read more

Effectiveness-Equity Models for Facility Location Problems on Tree Networks

We propose models to investigate effectiveness-equity tradeoffs in tree network facility location problems. We use the commonly used median objective as a measure of effectiveness, and the Gini index as a measure of (in)equity, and formulate bicriteria problems involving these objectives. We develop procedures to identify an efficient set of solutions to these problems, analyze … Read more

Solving mixed integer nonlinear programming problems for mine production planning with stockpiling

The open-pit mine production scheduling problem has received a great deal of attention in recent years, both in the academic literature, and in the mining industry. Optimization approaches to strategic planning for mine exploitation have become the industry standard. However most of these approaches focus on extraction sequencing, and don’t consider the material flow after … Read more

Minimum Concave Cost Flow Over a Grid Network

The minimum concave cost network flow problem (MCCNFP) is NP-hard, but efficient polynomial-time algorithms exist for some special cases such as the uncapacitated lot-sizing problem and many of its variants. We study the MCCNFP over a grid network with a general nonnegative separable concave cost function. We show that this problem is polynomially solvable when … Read more

Solving Bin Packing Related Problems Using an Arc Flow Formulation

We present a new method for solving bin packing problems, including two-constraint variants, based on an arc flow formulation with side constraints. Conventional formulations for bin packing problems are usually highly symmetric and provide very weak lower bounds. The arc flow formulation proposed provides a very strong lower bound, and is able to break symmetry … Read more

A Primal-Dual Algorithm for Computing a Cost Allocation in the Core of Economic Lot-Sizing Games

We consider the economic lot-sizing game with general concave ordering cost functions. It is well-known that the core of this game is nonempty when the inventory holding costs are linear. The main contribution of this work is a combinatorial, primal-dual algorithm that computes a cost allocation in the core of these games in polynomial time. … Read more

A Multi-Product Risk-Averse Newsvendor with Exponential Utility Function

We consider a multi-product newsvendor using an exponential utility function. We first establish a few basic properties for the newsvendor regarding the convexity of the model and monotonicity of the impact of risk aversion on the solution. When the product demands are independent and the ratio of the degree of risk aversion to the number … Read more

Computational and Economic Limitations of Dispatch Operations in the Next-Generation Power Grid

We study the interactions between computational and economic performance of dispatch operations under highly dynamic environments. In particular, we discuss the need for extending the forecast horizon of the dispatch formulation in order to anticipate steep variations of renewable power and highly elastic loads. We present computational strategies to solve the increasingly larger optimization problems … Read more

A parallel multi-population biased random-key genetic algorithm for a container loading problem

This paper presents a multi-population biased random-key genetic algorithm (BRKGA) for the Single Container Loading Problem (CLP) where several rectangular boxes of different sizes are loaded into a single rectangular container. The approach uses a maximal-space representation to manage the free spaces in the container. The proposed algorithm hybridizes a novel placement procedure with a … Read more