Flexible manufacturing systems: a review of analytical models
Management Science
Reducing the congestion in a class of job shops
Management Science
Capacity planning in manufacturing networks with discrete options
Annals of Operations Research
Concave minimization via conical partitions and polyhedral outer approximation
Mathematical Programming: Series A and B
A note on adapting methods for continuous global optimization to the discrete case
Annals of Operations Research
Separable concave minimization via partial outer approximation and branch and bound
Operations Research Letters
Heuristics for capacity planning problems with congestion
Computers and Operations Research
Inventory and distribution strategies for retail/e-tail organizations
Computers and Industrial Engineering
An algorithm for solving the multi-period online fulfillment assignment problem
Mathematical and Computer Modelling: An International Journal
| Hi-index | 0.98 |
This paper addresses capacity planning in systems that can be modeled as a network of queues. More specifically, we present an optimization model and solution methods for the minimum cost selection of capacity at each node in the network such that a set of system performance constraints is satisfied. Capacity is controlled through the mean service rate at each node. To illustrate the approach and how queueing theory can be used to measure system performance, we discuss a manufacturing model that includes upper limits on product throughput times and work-in-process in the system. Methods for solving capacity planning problems with continuous and discrete capacity options are discussed. We focus primarily on the discrete case with a concave cost function, allowing fixed charges and costs exhibiting economies of scale with respect to capacity to be handled.