Strategic and Tactical Planning Models for Supply Chain: An Application of Stochastic Mixed Integer Programming

2006 ◽  
pp. 227-264 ◽  
Author(s):  
Gautam Mitra ◽  
Chandra Poojari ◽  
Suvrajeet Sen
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Mixed Integer ◽  
Tactical Planning ◽  
Planning Models ◽  
Stochastic Mixed Integer Programming

Stochastic Mixed-Integer Programming for Integrated Portfolio Planning in the LNG Supply Chain

2014 ◽  
Vol 35 (1) ◽  
Author(s):  
Adrian Werner ◽  
Kristin Tolstad Uggen ◽  
Marte Fodstad ◽  
Arnt-Gunnar Lium ◽  
Ruud Egging
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Mixed Integer ◽  
Stochastic Mixed Integer Programming ◽  
Portfolio Planning

A bi-level programming for transportation services procurement based on combinatorial auction with fuzzy random parameters

2018 ◽  
Vol 30 (5) ◽  
pp. 1162-1182 ◽  
Author(s):  
Fang Yan ◽  
Yanfang Ma ◽  
Cuiying Feng
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Traditional Approach ◽  
Algorithm Analysis ◽  
Mixed Integer ◽  
Content Type ◽  
Winner Determination ◽  
Stochastic Mixed Integer Programming ◽  
Maximum Utility ◽  
Algorithm Comparison

Purpose The purpose of this paper is to study a transportation service procurement bid construction problem from a less than a full truckload perspective. It seeks to establish stochastic mixed integer programming to allow for the proper bundle of loads to be chosen based on price, which could improve the likelihood that carrier can earn its maximum utility. Design/methodology/approach The authors proposes a bi-level programming that integrates the bid selection and winner determination and a discrete particle swarm optimization (PSO) solution algorithm is then developed, and a numerical simulation is used to make model and algorithm analysis. Findings The algorithm comparison shows that although GA could find a little more Pareto solutions than PSO, it takes a longer time and the quality of these solutions is not dominant. The model analysis shows that compared with traditional approach, our model could promote the likelihood of winning bids and the decision effectiveness of the whole system because it considers the reaction of the shipper. Originality/value The highlights of this paper are considering the likelihood of winning the business and describing the conflicting and cooperative relationship between the carrier and the shipper by using a stochastic mixed integer programming, which has been rarely examined in previous research.

Sign in / Sign up

Export Citation Format

Share Document