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

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 impro...

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Bibliographic Details
Published in:Asia Pacific journal of marketing and logistics Vol. 30; no. 5; pp. 1162 - 1182
Main Authors: Yan, Fang, Ma, Yanfang, Feng, Cuiying
Format: Journal Article
Language:English
Published: Patrington Emerald Publishing Limited 30.11.2018
Emerald Group Publishing Limited
Subjects:
Algorithms
Auctions
Bids
Costs
Decision making
Game theory
Influence
Mathematical programming
Optimization
Prices
Profits
Studies
Transportation services
Discrete particle swarm optimization
Winner determination
Bi-level programming
Combinatorial transportation auctions
Fuzzy random
ISSN:1355-5855, 1758-4248
Online Access:Get full text
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Summary: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.
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ISSN:1355-5855
1758-4248
DOI:10.1108/APJML-07-2017-0154