An Economies-of-Scale Service System Design Problem

TL;DR

This paper addresses the complex design of service systems considering economies-of-scale, proposing a novel Lagrangian relaxation algorithm that efficiently optimizes facility placement, capacity, and customer allocation to minimize total costs.

Contribution

It introduces a general model with concave, non-decreasing opening cost functions and develops an efficient polynomial-time algorithm for solving it.

Findings

The algorithm effectively solves the model in computational experiments.

The approach handles general economies-of-scale cost functions.

Results demonstrate the method's efficiency and effectiveness.

Abstract

This paper studies the design of a service system in the presence of economies-of-scale. The goal is to make decision on the number, location, service capacities of facilities as well as on the allocation of customers to the opened facilities in order to minimize the cost of whole system. The total cost includes opening and serving costs of facilities aggregated to the transportation and waiting costs of customers. To reflect the economies-of-scale in the modeling, a general opening cost function is supposed for each service facility with the characteristic of being concave and non-decreasing on its service capacity. A Lagrangian relaxation algorithm is developed for solving the problem in its general form. The algorithm decomposes the relaxed model into some homogeneous subproblems where each one can be optimally solved in polynomial time with no need for any optimization solver. Our computational experiment shows that the developed algorithm is both efficient and effective in solving the proposed problem.