Extensions of labeling algorithms for multi‐objective uncertain shortest path problems

We consider multi-objective shortest path problems in which the edge lengths are uncertain. Different concepts for finding so-called robust efficient solutions for multi-objective robust optimization exist. In this article, we consider multi-scenario efficiency, flimsily and highly robust efficiency, and point-based and set-based minmax robust efficiency. Labeling algorithms are an important class of algorithms for multi-objective (deterministic) shortest path problems. We analyze why it is, for most of the considered concepts, not straightforward to use labeling algorithms to find robust efficient solutions. We then show two approaches to extend a generic multi-objective label correcting algorithm for these cases. We finally present extensive numerical results on the performance of the proposed algorithms.

[1]  L. G. Mitten Composition Principles for Synthesis of Optimal Multistage Processes , 1964 .

[2]  E. Martins On a multicriteria shortest path problem , 1984 .

[3]  H. W. Corley,et al.  Shortest paths in networks with vector weights , 1985 .

[4]  Matthias Ehrgott,et al.  A comparison of solution strategies for biobjective shortest path problems , 2009, Comput. Oper. Res..

[5]  Cécile Murat,et al.  Robust Shortest Path Problems , 2010 .

[6]  E. Polak,et al.  On Multicriteria Optimization , 1976 .

[7]  Anita Schöbel,et al.  Generalized light robustness and the trade-off between robustness and nominal quality , 2014, Math. Methods Oper. Res..

[8]  W. Matthew Carlyle,et al.  Near-shortest and K-shortest simple paths , 2005 .

[9]  G. Bitran Linear Multiple Objective Problems with Interval Coefficients , 1980 .

[10]  Vincent Blouin,et al.  Multi-criteria Multi-scenario Approaches in the Design of Vehicles , 2005 .

[11]  Nikolaos Trichakis,et al.  Pareto Efficiency in Robust Optimization , 2014, Manag. Sci..

[12]  J. M. Paixão,et al.  Labeling Methods for the General Case of the Multi-objective Shortest Path Problem – A Computational Study , 2013 .

[13]  Anita Schöbel,et al.  Dominance for multi-objective robust optimization concepts , 2019, Eur. J. Oper. Res..

[14]  Richard Bellman,et al.  ON A ROUTING PROBLEM , 1958 .

[15]  R. Musmanno,et al.  Label Correcting Methods to Solve Multicriteria Shortest Path Problems , 2001 .

[16]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[17]  J. Meigs,et al.  WHO Technical Report , 1954, The Yale Journal of Biology and Medicine.

[18]  T. A. Brown,et al.  Dynamic Programming in Multiplicative Lattices , 1965 .

[19]  Ishwar Murthy,et al.  Solving min‐max shortest‐path problems on a network , 1992 .

[20]  Andrea Raith,et al.  Multi-objective minmax robust combinatorial optimization with cardinality-constrained uncertainty , 2017, Eur. J. Oper. Res..

[21]  D. Shier,et al.  An empirical investigation of some bicriterion shortest path algorithms , 1989 .

[22]  Mordechai I. Henig,et al.  The Principle of Optimality in Dynamic Programming with Returns in Partially Ordered Sets , 1985, Math. Oper. Res..

[23]  Patrice Perny,et al.  A preference-based approach to spanning trees and shortest paths problems**** , 2005, Eur. J. Oper. Res..

[24]  Andrea Raith,et al.  Bi-objective robust optimisation , 2016, Eur. J. Oper. Res..

[25]  R. Werner Robust Multiobjective Optimization , 2015 .

[26]  Alfredo Candia-Véjar,et al.  Minmax regret combinatorial optimization problems: an Algorithmic Perspective , 2011, RAIRO Oper. Res..

[27]  Daniel Vanderpooten,et al.  Min-max and min-max regret versions of combinatorial optimization problems: A survey , 2009, Eur. J. Oper. Res..

[28]  Yang Jian,et al.  On the robust shortest path problem , 1998, Comput. Oper. Res..

[29]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[30]  Margaret M. Wiecek,et al.  Robust Multiobjective Optimization for Decision Making Under Uncertainty and Conflict , 2016 .

[31]  A. Schöbel,et al.  The relationship between multi-objective robustness concepts and set-valued optimization , 2014 .

[32]  Harold P. Benson,et al.  On a domination property for vector maximization with respect to cones , 1984 .

[33]  Roberto Montemanni,et al.  The robust shortest path problem with interval data via Benders decomposition , 2005, 4OR.

[34]  Luis C. Dias,et al.  Shortest path problems with partial information: Models and algorithms for detecting dominance , 2000, Eur. J. Oper. Res..

[35]  Matthias Ehrgott,et al.  Minmax robustness for multi-objective optimization problems , 2014, Eur. J. Oper. Res..

[36]  Trivikram Dokka,et al.  An Experimental Comparison of Uncertainty Sets for Robust Shortest Path Problems , 2017, ATMOS.

[37]  T. Morin Monotonicity and the principle of optimality , 1982 .

[38]  Anita Schöbel,et al.  Robustness for uncertain multi-objective optimization: a survey and analysis of different concepts , 2016, OR Spectr..

[39]  Kim Allan Andersen,et al.  A label correcting approach for solving bicriterion shortest-path problems , 2000, Comput. Oper. Res..

[40]  Marta M. B. Pascoal,et al.  The minmax regret robust shortest path problem in a finite multi-scenario model , 2014, Appl. Math. Comput..

[41]  Rasmus Bokrantz,et al.  Necessary and sufficient conditions for Pareto efficiency in robust multiobjective optimization , 2013, Eur. J. Oper. Res..

[42]  Melvyn Sim,et al.  Robust discrete optimization and network flows , 2003, Math. Program..