A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. O...

We present novel branch-and-check and logic-based Benders decomposition techniques for the Travelling Purchaser Problem, an important optimization problem with applications in vehicle routing, logistics, and warehouse management. Our master problem determines a set of markets and directed travel arcs that satisfy product purchase constraints with relaxed travel costs. Our subproblem identifies ...

The vehicle routing problem (VRP) is an important problem in the field of logistics management. As an NP-hard problem, the VRP real world sized instances cannot be solved to optimality within reasonable times. This research aims to develop a two-stage ant colony optimization (TACO) algorithm, which possesses a two-stage solution construction rule, to solve the large scale vehicle routing proble...

This paper presents the development of a novel vehicle-routing-based algorithm for optimizing component pick-up and placement on a collect-and-place type machine in printed circuit board manufacturing. We present a two-phase heuristic that produces solutions of remarkable quality with respect to other known approaches in a reasonable amount of computational time. In the first phase, a construct...

We have created a framework that provides a way to represent a wide range of scheduling and assignment problems across many domains. We have also created an optimizing scheduler that can, without modification, solve any problem represented using this framework. The three components of a problem representation are the metadata, the data, and the scheduling semantics. The scheduler performs the o...

Ant Colony Optimization is a relatively new meta-heuristic that has proven its quality and versatility on various combinatorial optimization problems such as the traveling salesman problem, the vehicle routing problem and the job shop scheduling problem. The paper introduces an Ant Colony Optimization approach to solve the problem of determining a job-sequence that minimizes the overall tardine...

The General Routing Problem (GRP) is the problem of finding a minimum cost route for a single vehicle, subject to the condition that the vehicle visits certain vertices and edges of a network. It contains the Rural Postman Problem, Chinese Postman Problem and Graphical Travelling Salesman Problem as special cases. We describe a cutting plane algorithm for the GRP based on facet-inducing inequal...

Ant Colony Optimization is a relatively new meta-heuristic that has proven its quality and versatility on various combinatorial optimization problems such as the traveling salesman problem, the vehicle routing problem and the job shop scheduling problem. The paper introduces an Ant Colony Optimization approach to solve the problem of determining a job-sequence that minimizes the overall tardine...