An Integrated Scenario-Based Approach for Robust Aircraft Routing, Crew Pairing and Re-timing.

For reasons of tractability, the airline scheduling problem has traditionally been sequentially decomposed into various stages (eg. schedule generation, fleet assignment, aircraft routing, and crew pairing), with the decisions from one stage imposed upon the decision making process in subsequent stages. Whilst this approach greatly simplifies the solution process, it unfortunately fails to capture the … Read more

Composite Retrieval of Diverse and Complementary Bundles

Users are often faced with the problem of finding complementary items that together achieve a single common goal (e.g., a starter kit for a novice astronomer, a collection of question/answers related to low-carb nutrition, a set of places to visit on holidays). In this paper, we argue that for some application scenarios returning item bundles … Read more

Traveling Salesman Problem Formulations with \log N$ Number of Binary Variables

Abstract This paper presents a novel formulation for the Traveling Salesman Problem (TSP), utilizing a binary list data-structure allocating cities to its leaves to form sequentially the tour of the problem. The structure allows the elimination of subtours from the formulation and at the same time reducing the number of binary variables to ${\cal O}(N\log_{2}N)$. … Read more

A big bucket time indexed formulation for nonpreemptive single machine scheduling problems

A big bucket time indexed mixed integer linear programming formulation for nonpreemptive single machine scheduling problems is presented in which the length of each period can be as large as the processing time of the shortest job. The model generalises the classical time indexed model to one in which at most two jobs can be … Read more

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

Shipping Data Generation for the Hunter Valley Coal Chain

Strategic capacity planning is a core activity for the Hunter Valley Coal Chain Coordinator as demand for coal is expected to double in the next decade. Optimization and simulation models are used to suggest and evaluate infrastructure expansions and operating policy changes. These models require input data in the form of shipping stems, which are … 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

Asset Allocation under the Basel Accord Risk Measures

Financial institutions are currently required to meet more stringent capital requirements than they were before the recent financial crisis; in particular, the capital requirement for a large bank’s trading book under the Basel 2.5 Accord more than doubles that under the Basel II Accord. The significant increase in capital requirements renders it necessary for banks … Read more

A two-step optimization approach for job shop scheduling problem using a genetic algorithm

This paper presents a two-step optimization approach to solve the complex scheduling problem in a job shop environment. This problem is also known as the Job Shop Scheduling Problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The proposed approach … Read more