A Decomposition Approach to the Inventory Routing Problem with Satellite Facilities
Transportation Science
Decomposition of a Combined Inventory and Time Constrained Ship Routing Problem
Transportation Science
Synchronized Development of Production, Inventory, and Distribution Schedules
Transportation Science
A column generation approach to the heterogeneous fleet vehicle routing problem
Computers and Operations Research
A reactive GRASP and path relinking for a combined production-distribution problem
Computers and Operations Research
An optimization algorithm for the inventory routing problem with continuous moves
Computers and Operations Research
A Branch-and-Cut Algorithm for a Vendor-Managed Inventory-Routing Problem
Transportation Science
The integrated production---inventory---distribution---routing problem
Journal of Scheduling
Heuristics for a multiperiod inventory routing problem with production decisions
Computers and Industrial Engineering
Supply chain system design integrated with risk pooling
Computers and Industrial Engineering
A local search method for periodic inventory routing problem
Expert Systems with Applications: An International Journal
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With globalization, the need to better integrate production and distribution decisions has become ever more pressing for manufacturers trying to streamline their supply chain. This paper investigates a previously developed mixed-integer programming (MIP) model aimed at minimizing production, inventory, and delivery costs across the various stages of the system. The problem being modeled includes a single production facility, a set of customers with time varying demand, a finite planning horizon, and a fleet of homogeneous vehicles. Demand can be satisfied from either inventory held at a customer site or from daily product distribution. Whether a customer is visited on a particular day is determined by an implicit tradeoff between inventory and distribution costs. Once the decision is made, a vehicle routing problem must be solved for those customers who are scheduled for a delivery. A hybrid methodology that combines exact and heuristic procedures within a branch-and-price framework is developed to solve the underlying MIP. The approach takes advantage of the efficiency of heuristics and the precision of branch and price. Implementation required devising a new branching strategy to accommodate the unique degeneracy characteristics of the master problem, and a new procedure for handling symmetry. A novel column generation heuristic and a rounding heuristic were also implemented to improve algorithmic efficiency. Computational testing on standard data sets showed that the hybrid scheme can solve instances with up to 50 customers and 8 time periods within 1h. This level of performance could not be matched by either CPLEX or standard branch and price alone.