Multi-objective Optimization Based Algorithms for Solving Mixed Integer Linear Minimum Multiplicative Programs

We present two new algorithms for a class of single-objective non-linear optimization problems, the so-called Mixed Integer Linear minimum Multiplicative Programs (MIL-mMPs). This class of optimization problems has a desirable characteristic: a MIL-mMP can be viewed as a special case of the problem of optimization over the efficient set in multi-objective optimization. The proposed algorithms … Read more

A bi-level branch-and-bound algorithm for the capacitated competitive facility location problem

Competitive facility location problem is a typical facility locating optimization problem but in a competitive environment. The main characteristic of this problem is the competitive nature of the market. In essence, the problem involves two competitors, i.e., a leader and a follower, who seek to attract customers by establishing new facilities to maximize their own … Read more

Hybrid Rebalancing with Dynamic Hubbing for Free-floating Bike Sharing Using Multi-objective Simulation Optimization

For rebalancing problem of free-floating bike sharing systems, we propose dynamic hubbing (i.e. dynamically determining geofencing areas) and hybrid rebalancing (combining user-based and operator-based strategies) and solve the problem with a novel multi-objective simulation optimization approach. Given historical usage data and real-time bike GPS location information, dynamic geofenced areas (hubs) are determined to encourage users … Read more

Free-Floating Bike Sharing: Solving Real-life Large-scale Static Rebalancing Problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the … Read more

Reliable p-median facility location problem: two-stage robust models and algorithms

In this paper, we propose a set of two-stage robust optimization models to design reliable p-median facility location networks subject to disruptions. A customized column-and- constraint generation approach is implemented and shown to be more effective than Benders cutting plane method. Numerical experiments are performed on real data and management insights on system design are … Read more

The Reliable Hub-and-spoke Design Problem: Models and Algorithms

This paper presents a study on reliable single and multiple allocation hub-and-spoke network design problems where disruptions at hubs and the resulting hub unavailability can be mitigated by backup hubs and alternative routes. It builds nonlinear mixed integer programming models and presents linearized formulas. To solve those difficult problems, Lagrangian relaxation and Branch-and-Bound methods are … Read more