A comparison of different solution approaches to the vehicle scheduling problem in a practical case

Managerial and Decision EconomicsVolume 11, Issue 3 p. 211-212 Call for Paper European Journal of Operational Research. A special issue on model validation in operations research First published: 1990 https://doi.org/10.1002/mde.4090110309AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume11, Issue31990Pages 211-212 RelatedInformation

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Heuristic approaches for solving transit vehicle scheduling problem with route and fueling time constraints

Optimal Multi-Vehicle Type Transit Timetabling and Vehicle Scheduling

In this paper, the ant colony algorithms is studied, and improve the shortcomings of the algorithm, And the improved algorithm is introduced into the field of logistics transportation.Aiming at the complexity and uncertainty of logistics transportation vehicle scheduling problem, a new algorithm is designed.The experimental results show that the improved algorithm can choose the transport route, speed up the transportation speed, improve the service quality, reduce the transportation cost and increase economic benefits.

This paper describes an integer programming formulation of the vehicle scheduling problem and illustrates how such a formulation can be extended to incorporate restrictions on work load, coverage and service that occur in real world vehicle scheduling problems. The integer programme is solved using the Revised Simplex method, additional constraints being introduced to retain integrality during convergence. The feasible region of this integer programme is initially restricted so that only routes constructed through sets of radially contiguous locations are considered. The effect of relaxing these over-constraints is explored. The method is demonstrated on fifteen problems ranging in size from 21 to 100 locations and the results generally show an improvement on previously published results. This is particularly true of the larger problems. This method compares favourably with other methods in computational efficiency.

Contributors

A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem

Developing new formulations and relaxations of single stage capacitated warehouse location problem (SSCWLP): Empirical investigation for assessing relative strengths and computational effort

We propose a novel joint pricing and lot sizing model to enable manufacturers plan production and pricing. These types of models have proven to be very popular and are collectively known as the Joint Pricing and Lot sizing Models. We include a discount factor in our model to increase profit for the manufacturer. Our proposed model relies on the fact that demand influences production cost indirectly, while it is dependent on price and the discount offered. By considering the form of demand and production cost, it is apparent that the presented model is a Signomial Geometric Programming problem. We obtain optimal solutions for price, lot size and discount factor by applying the modified transformation method of geometric programming. Numerical examples, which include sensitivity analysis of the objective function and parameters, illustrate our model. References C. J. Corbett and X. de Groote. A supplier's optimal quantity discount policy under asymmetric information. Management Science, 46(3):444--450, 2000. R. J Duffin, E. L Peterson, and C. Zener. Geometric programming, Theory and Application. John Wiely and Sons, 1967. J. R. Freeland. Coordination strategies for production and marketing in a functionally decentralized firm. AIIE Transactions, 12:126--132, 1982. Woon J.Lee, Daesoo Kim, and A. Cabot. Optimal demand rate, lot sizing, and process reliability improvement decisions. IIE Transactions, 28:941--952, 1996. http://cat.inist.fr/?aModele=afficheN&cpsidt=2490704. Daesoo Kim and Woon J. Lee. Optimal joint pricing and lot sizing with fixed and variable capacity. European Journal of Operational Research, 109(1):212--227, 1998. http://www.sciencedirect.com/science/article/B6VCT-3TMR6M6-H/2/2d166a9b5fc0a9a27e923c495f256663. Woon J. Lee. Determining order quantity and selling price by geometric programming. Decision Sciences, 24:76--87, 1993. doi:10.1111/j.1540-5915.1993.tb00463.x. Woon J. Lee and Daesoo Kim. Optimal and heuristic decision strategies for integrated product and marketing planning. Decision Sciences, 24(6):1203--1213, 1993, doi:10.1111/j.1540-5915.1993.tb00511.x. Seyed J. Sajadi, Maryam Orouge, and M. B. Aryanezhad. Optimal production and marketing planning. Computational Optimization and Applications, 30(2):195--203, 2005. http://portal.acm.org/citation.cfm?id=1062644.1062668. Richard J. Tersine. Principles of Inventory And Materials Management. PTR Prentice Hall, Englewood Cliffs, New Jersey 07632, 1994. S. Viswanathan and Q.Wang. Discount pricing decisions in distribution channels with price sensitive demand. European Journal of Operational Research, 149(3):571--587, 2003. http://ideas.repec.org/a/eee/ejores/v149y2003i3p571-587.html. Prakash L. Abad. Determining optimal selling price and the lot size when the supplier offers all-unit quantity discounts. Decision Sciences, 3(19):622--634, 1988. Z. Kevin Weng. Channel coordination and quantity discounts. Management Sciences, 41(9):1509--1522, 1995. http://www.jstor.org/view/00251909/di012962/01p03025/0. Prakash L. Abad. Supplier pricing and lot sizing when demand is price sensitive. European Journal of Operational Research, (78):334--354, 1994. http://cat.inist.fr/?aModele=afficheN&cpsidt=3309143. Charles S. Beightler. Applied Geometric Programming. John Wiely and Sons, 1976. C. W. Chiang, J. Fitzsimmons, Z. Huang, and S. Li. A game theoretic approach to quantity discount problem. Decision Sciences, 25(1):153--168, 1994. doi:10.1111/j.1540-5915.1994.tb00521.x.

Reply to the note on article “The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees”

Performance evaluation of bus routes: A provider and passenger perspective

Single-machine scheduling against due dates with past-sequence-dependent setup times

Previous articleNext article No AccessDiscussionEthics, Ideals, and DissatisfactionC. West ChurchmanC. West Churchman Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Ethics Volume 63, Number 1Oct., 1952 Article DOIhttps://doi.org/10.1086/290861 Views: 2Total views on this site Citations: 4Citations are reported from Crossref Copyright 1952 The University of ChicagoPDF download Crossref reports the following articles citing this article:Mike Walsh, Markus G. Kittler, Dawn Mahal Towards a new paradigm of healthcare: Addressing challenges to professional identities through Community Operational Research, European Journal of Operational Research 268, no.33 (Aug 2018): 1125–1133.https://doi.org/10.1016/j.ejor.2017.05.052Arjang A. Assad C. West Churchman, (Feb 2011): 171–200.https://doi.org/10.1007/978-1-4419-6281-2_11Norma R.A. Romm The Social Significance of Churchman’s Epistemological Position, (Jan 2006): 68–92.https://doi.org/10.1007/0-387-27589-4_6Rachel S. Sutton An Analysis of Factors Related to Educational Achievement, The Journal of Genetic Psychology 98, no.22 (Jun 1961): 193–201.https://doi.org/10.1080/00221325.1961.10534369

An inventory model under inflation for deteriorating items with stock-dependent consumption rate and partial backlogging shortages