A Hybrid MCDM Approach to Transshipment Port Selection

Port selection is an intrinsic supply-chain problem that has substantial impact on development of local economies. Shipping business environment developed into complex system where decision making is derived from uncertain and incomplete data. In this study we present a conceptual integrated MultiCriteria decision solution to transshipment port selection problem based on Best-Worst MCdM and Artificial Bee Colony Algorithm. Through literature review and expert analysis, 50 relevant criteria have been identified as relevant to the transshipment port selection problem. decision makers within liner shipping companies evaluate transshipment port selection criteria and establish ranking that is used to determine crisp solution with lowest consistency ratio. ABC based algorithm is used to reduce computational complexity and deliver a single optimal solution by solving both objective and constraint violation functions.

[1]  Bernard Roy,et al.  Classement et choix en présence de points de vue multiples , 1968 .

[2]  Dimitrios A Tsamboulas,et al.  Use of Multicriteria Methods for Assessment of Transport Projects , 1999 .

[3]  Christopher R. Houck,et al.  On the use of non-stationary penalty functions to solve nonlinear constrained optimization problems with GA's , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[4]  Dervis Karaboga,et al.  Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems , 2007, IFSA.

[5]  Bertrand Mareschal,et al.  Prométhée: a new family of outranking methods in multicriteria analysis , 1984 .

[6]  Gwo-Hshiung Tzeng,et al.  Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS , 2004, Eur. J. Oper. Res..

[7]  Lothar Thiele,et al.  A Comparison of Selection Schemes used in Genetic Algorithms , 1995 .

[8]  Anthony Kenneth Charles Beresford,et al.  Transhipment Port Selection and Decision-making Behaviour: Analysing the Taiwanese Case , 2003 .

[9]  Waldemar W. Koczkodaj,et al.  A Monte Carlo Study of Pairwise Comparisons , 2015, ArXiv.

[10]  Marko Gulić,et al.  Nature Inspired Metaheuristics for Optimizing Problems at a Container Terminal , 2018 .

[11]  Michael N. Vrahatis,et al.  Unified Particle Swarm Optimization for Solving Constrained Engineering Optimization Problems , 2005, ICNC.

[12]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[13]  Theodor J. Stewart,et al.  Multiple criteria decision analysis - an integrated approach , 2001 .

[14]  David L. Olson,et al.  Comparison of weights in TOPSIS models , 2004, Math. Comput. Model..

[15]  Edmundas Kazimieras Zavadskas,et al.  Multiple criteria decision-making techniques in transportation systems: a systematic review of the state of the art literature , 2015 .

[16]  Dung-Ying Lin,et al.  An equilibrium-based network model for international container flows , 2017 .

[17]  Anthony Kenneth Charles Beresford,et al.  An Application of AHP on Transhipment Port Selection: A Global Perspective , 2004 .

[18]  Jairo R. Montoya-Torres,et al.  Multi-criteria approaches for urban passenger transport systems: a literature review , 2015, Ann. Oper. Res..

[19]  Koi Yu Adolf Ng.  Assessing the Attractiveness of Ports in the North European Container Transhipment Market: An Agenda for Future Research in Port Competition , 2006 .

[20]  P. Vincke,et al.  Note-A Preference Ranking Organisation Method: The PROMETHEE Method for Multiple Criteria Decision-Making , 1985 .

[21]  Dong-Wook Song,et al.  An Application of the Hierarchical Fuzzy Process to Container Port Competition: Policy and Strategic Implications , 2006 .

[22]  Paulius Kavaliauskas,et al.  A concept of sustainable development for regional land use planning: Lithuanian experience , 2008 .

[23]  T. L. Saaty.  A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[24]  Umut Asan,et al.  A new rule-based integrated decision making approach to container transshipment terminal selection , 2018, Maritime Policy & Management.

[25]  Ernest H. Forman,et al.  Decision By Objectives: How To Convince Others That You Are Right , 2001 .

[26]  Chien-Chang Chou,et al.  Application of FMCDM model to selecting the hub location in the marine transportation: A case study in southeastern Asia , 2010, Math. Comput. Model..

[27]  Ching-Lai Hwang,et al.  A new approach for multiple objective decision making , 1993, Comput. Oper. Res..

[28]  Michel Gendreau,et al.  A guide to vehicle routing heuristics , 2002, J. Oper. Res. Soc..

[29]  Čedomir Dundović,et al.  Criteria for Selecting a Location for a Port of Nautical Tourism , 2009 .

[30]  Stanislav Karapetrovic,et al.  A quality control approach to consistency paradoxes in AHP , 1999, Eur. J. Oper. Res..

[31]  Tomislav Rožić,et al.  Decision Making Background for the Location of Inland Terminals , 2016 .

[32]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[33]  Hamed Hasheminia,et al.  Strategic trade-off between vessel delay and schedule recovery: an empirical analysis of container liner shipping , 2017 .

[34]  Xiaohui Hu,et al.  Engineering optimization with particle swarm , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[35]  T. Saaty.  How to Make a Decision: The Analytic Hierarchy Process , 1990 .

[36]  Russell C. Eberhart,et al.  Solving Constrained Nonlinear Optimization Problems with Particle Swarm Optimization , 2002 .

[37]  Zaili Yang,et al.  Modelling port choice in an uncertain environment , 2014 .

[38]  Samia Nefti-Meziani,et al.  A Comprehensive Review of Swarm Optimization Algorithms , 2015, PloS one.

[39]  Li-Pei Wong,et al.  An efficient Bee Colony Optimization algorithm for Traveling Salesman Problem using frequency-based pruning , 2009, 2009 7th IEEE International Conference on Industrial Informatics.

[40]  T. Saaty.  Axiomatic foundation of the analytic hierarchy process , 1986 .

[41]  Panos M. Pardalos,et al.  A Collection of Test Problems for Constrained Global Optimization Algorithms , 1990, Lecture Notes in Computer Science.

[42]  Masao Fukushima,et al.  Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization , 2006, J. Glob. Optim..

[43]  Jean Pierre Brans,et al.  HOW TO SELECT AND HOW TO RANK PROJECTS: THE PROMETHEE METHOD , 1986 .

[44]  Chien-Chang Chou,et al.  A fuzzy MCDM method for solving marine transshipment container port selection problems , 2007, Appl. Math. Comput..

[45]  A. Jugović,et al.  THE ROLE AND APPLICABILITY OF MULTI-CRITERIA PROCEDURES IN THE FUNCTION OF DEFINING THE MODEL FOR CONNECTING THE MAINLAND AND ISLANDS AND ISLANDS IN BETWEEN , 2015 .

[46]  Innocent C. Ogwude,et al.  An Analytic Hierarchy Process (AHP) Approach to Port Selection Decisions – Empirical Evidence from Nigerian Ports , 2006 .

[47]  Behzad Nozohour-leilabady,et al.  On the application of artificial bee colony (ABC) algorithm for optimization of well placements in fractured reservoirs; efficiency comparison with the particle swarm optimization (PSO) methodology , 2016 .

[48]  L. Thurstone.  A law of comparative judgment. , 1994 .

[49]  J. Rezaei.  Best-worst multi-criteria decision-making method , 2015 .

[50]  J. Rezaei,et al.  A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method , 2016 .

[51]  Der-Horng Lee,et al.  Schedule Template Design and Storage Allocation for Cyclically Visiting Feeders in Container Transshipment Hubs , 2012 .

[52]  Hayri Baraçli,et al.  An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul , 2013 .

[53]  B. Roy.  The outranking approach and the foundations of electre methods , 1991 .