Service system design with immobile servers, stochastic demand and concave-cost capacity selection

DOI10.1016/j.cor.2018.01.019zbMath1391.90181OpenAlexW2787928828MaRDI QIDQ1652604

Ahmed Saif, Yan Wang, Samir Elhedhli

Publication date: 11 July 2018

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2018.01.019

zbMATH Keywords

Lagrangian relaxationservice system designsecond-order cone programming\(M/M/1\)economies-of-scalespecial order sets of type 2 (SOS2)

Mathematics Subject Classification ID

Semidefinite programming (90C22) Queueing theory (aspects of probability theory) (60K25) Queues and service in operations research (90B22) Applications of queueing theory (congestion, allocation, storage, traffic, etc.) (60K30)

Related Items (5)

Robust design of service systems with immobile servers under demand uncertainty ⋮ A portfolio optimization approach to design of congested multi‐service networks with application in community healthcare: fractional 0‐1 programming ⋮ An efficient optimization procedure for location-inventory problems with (S-1, S) policy and retrial demands ⋮ Service expansion for chained business facilities under congestion and market competition ⋮ Modeling and solving an economies‐of‐scale service system design problem

Cites Work

• Unnamed Item
• Unnamed Item
• Cold supply chain design with environmental considerations: a simulation-optimization approach
• Efficient solution of a class of location-allocation problems with stochastic demand and congestion
• Supply chain design considering economies of scale and transport frequencies
• Exact solution of a class of nonlinear knapsack problems
• The design of service systems with queueing time cost, workload capacities and backup service
• A production-transportation problem with stochastic demand and concave production costs
• Solution procedures for the service system design problem
• Queueing models of call centers: An introduction
• Algorithms for a facility location problem with stochastic customer demand and immobile servers
• A multiple server location-allocation model for service system design
• A Lagrangian heuristic for concave cost facility location problems: the plant location and technology acquisition problem
• What you should know about queueing models to set staffing requirements in service systems
• Heavy-Traffic Limits for Queues with Many Exponential Servers
• Global optimization using special ordered sets
• Optimal Facility Location with Concave Costs
• Deterministic Production Planning with Concave Costs and Capacity Constraints

This page was built for publication: Service system design with immobile servers, stochastic demand and concave-cost capacity selection