Application of a hybrid intelligent decision support model in logistics outsourcing

Outsourcing is an increasingly important issue pursued by corporations seeking improved efficiency. Logistics outsourcing or third-party logistics (3PL) involves the use of external companies to perform some or all of the firm's logistics activities. This paper proposes an intelligent decision support framework for effective 3PL evaluation and selection. The proposed framework integrates case-based reasoning, rule-based reasoning and compromise programming techniques in fuzzy environment. This real-time decision-making approach deals with uncertain and imprecise decision situations. Furthermore, the integration of different methodologies takes the advantage of their strengths and complements each other's weaknesses. Consequently, the framework leads to a more accurate, flexible and efficient retrieval of 3PL service providers (alternatives) that are most similar and most useful to the current decision situation. Finally, a real industrial application is given to demonstrate the potential of the proposed framework.

[1]  Shu-Hsuan Chang,et al.  Applying case-based reasoning for product configuration in mass customization environments , 2005, Expert Syst. Appl..

[2]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1989, IJCAI 1989.

[3]  Jae Kyu Lee,et al.  An effective customization procedure with configurable standard models , 2005, Decis. Support Syst..

[4]  Kin Keung Lai,et al.  A fuzzy approach to the multiobjective transportation problem , 2000, Comput. Oper. Res..

[5]  Yosef Sheffi,et al.  THIRD PARTY LOGISTICS -- PRESENT AND FUTURE PROSPECTS , 1990 .

[6]  Ching-Hsue Cheng,et al.  Selecting IS personnel use fuzzy GDSS based on metric distance method , 2005, Eur. J. Oper. Res..

[7]  Robert Millen,et al.  Third Party Logistics Services: A Comparison of Experienced American and European Manufacturers , 1993 .

[8]  Maria Meler-Kapcia,et al.  CBR methodology application in an expert system for aided design ship's engine room automation , 2005, Expert Syst. Appl..

[9]  Luca Spalzzi,et al.  A Survey on Case-Based Planning , 2001 .

[10]  Marcus Jefferies,et al.  A strategy for evaluating a fuzzy case-based construction procurement selection system , 2006, Adv. Eng. Softw..

[11]  Matthias Ehrgott,et al.  Computation of ideal and Nadir values and implications for their use in MCDM methods , 2003, Eur. J. Oper. Res..

[12]  Ching-Yuen Chan,et al.  Process design for transfer moulding of electronic packages using a case-based reasoning approach with fuzzy regression adaptation , 2005, Int. J. Comput. Integr. Manuf..

[13]  S. Wesley Changchien,et al.  Design and implementation of a case-based reasoning system for marketing plans , 2005, Expert systems with applications.

[14]  M. Razzaque,et al.  Outsourcing of logistics functions: a literature survey , 1998 .

[15]  G. G. Merino,et al.  Fuzzy compromise programming with precedence order in the criteria , 2003, Appl. Math. Comput..

[16]  Luca Spalazzi,et al.  A Survey on Case-Based Planning , 2004, Artificial Intelligence Review.

[17]  Ganesh Vaidyanathan,et al.  A framework for evaluating third-party logistics , 2005, CACM.

[18]  Melvyn Peters,et al.  Third‐party logistics in Europe – five years later , 2000 .

[19]  Amrik S. Sohal,et al.  The use of third party logistics services: a Malaysian perspective , 2003 .

[20]  M. Zeleny.  Linear Multiobjective Programming , 1974 .

[21]  Simon C. K. Shiu,et al.  A Tutorial on Case Based Reasoning , 2000, Soft Computing in Case Based Reasoning.

[22]  Sohail S. Chaudhry,et al.  A model of a decision support system based on case‐based reasoning for third‐party logistics evaluation , 2003, Expert Syst. J. Knowl. Eng..

[23]  Amelia Bilbao-Terol,et al.  Solving a multiobjective possibilistic problem through compromise programming , 2005, Eur. J. Oper. Res..

[24]  Shian-Shyong Tseng,et al.  Design and implementation of new object-oriented rule base management system , 2003, Expert Syst. Appl..

[25]  GeunSik Jo,et al.  Case-based tutoring systems for procedural problem solving on the www , 2005, Expert Syst. Appl..

[26]  Minyong Kim,et al.  MyMessage: case-based reasoning and multicriteria decision making techniques for intelligent context-aware message filtering , 2004, Expert Syst. Appl..

[27]  Chen-Tung Chen,et al.  A fuzzy approach for supplier evaluation and selection in supply chain management , 2006 .

[28]  Fong-Yuen Ding,et al.  Using data envelopment analysis to compare suppliers for supplier selection and performance improvement , 2000 .

[29]  Steven A. Melnyk,et al.  Applying environmental criteria to supplier assessment: A study in the application of the Analytical Hierarchy Process , 2002, Eur. J. Oper. Res..

[30]  Lucien Duckstein,et al.  Composite Programming as an Extension of Compromise Programming , 1985 .

[31]  Henry C. W. Lau,et al.  A knowledge-based supplier intelligence retrieval system for outsource manufacturing , 2005, Knowl. Based Syst..

[32]  Zhiming Zhang,et al.  Similarity Measures for Retrieval in Case-Based Reasoning Systems , 1998, Appl. Artif. Intell..

[33]  Ni-Bin Chang,et al.  Corporate optimal production planning with varying environmental costs: A grey compromise programming approach , 2004, Eur. J. Oper. Res..

[34]  Michela Bertolotto,et al.  Digital Image Similarity for Geo-spatial Knowledge Management , 2002, ECCBR.

[35]  Bor-Wen Cheng,et al.  Using case-based reasoning to establish a continuing care information system of discharge planning , 2004, Expert Syst. Appl..

[36]  Yoram Reich,et al.  A framework for organizing the space of decision problems with application to solving subjective, context-dependent problems , 2005, Decis. Support Syst..

[37]  Richard Wilding,et al.  Customer perceptions on logistics outsourcing in the European consumer goods industry , 2004 .

[38]  W. B. Lee,et al.  Design of a case based intelligent supplier relationship management system - the integration of supplier rating system and product coding system , 2003, Expert Syst. Appl..

[39]  Felix T. S. Chan,et al.  Design of a knowledge-based logistics strategy system , 2005, Expert Syst. Appl..

[40]  George Bojadziev,et al.  Fuzzy Sets, Fuzzy Logic, Applications , 1996, Advances in Fuzzy Systems - Applications and Theory.

[41]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[42]  P. C. Wright,et al.  A practical guide to successful outsourcing , 1998 .

[43]  Ronald R. Yager,et al.  Competitiveness and compensation in decision making: A fuzzy set based interpretation , 1980, Comput. Oper. Res..

[44]  Felix T. S. Chan,et al.  Application of a hybrid case-based reasoning approach in electroplating industry , 2005, Expert Syst. Appl..

[45]  John N. Pearson,et al.  The impact of purchasing and supplier involvement on strategic purchasing and its impact on firm’s performance , 2002 .

[46]  A. Bárdossy,et al.  Analysis of a karstic aquifer management problem by fuzzy composite programming , 1992 .

[47]  Komaragiri Srinivasa Raju,et al.  Multicriterion decision making in river basin planning and development , 1999, Eur. J. Oper. Res..

[48]  Sankar K. Pal,et al.  Soft Computing in Case Based Reasoning , 2000, Springer London.

[49]  Gilles Paché,et al.  Logistics outsourcing in grocery distribution: a European perspective , 1998 .

[50]  Paul R. Murphy,et al.  THIRD-PARTY LOGISTICS: SOME USER VERSUS PROVIDER PERSPECTIVES. , 2000 .

[51]  Carl W. Entemann.  Fuzzy Logic: Misconceptions and Clarifications , 2002, Artificial Intelligence Review.

[52]  Ravi Shankar,et al.  Selection of logistics service provider: An analytic network process (ANP) approach , 2007 .