SIMHEURISTICS APPLICATIONS: DEALING WITH UNCERTAINTY IN LOGISTICS, TRANSPORTATION, AND OTHER SUPPLY CHAIN AREAS

Optimization problems arising in real-life transportation and logistics need to consider uncertainty conditions (e.g., stochastic travel times, etc.). Simulation is employed in the analysis of complex systems under such non-deterministic environments. However, simulation is not an optimization tool, so it needs to be combined with optimization methods whenever the goal is to: (i) maximize the system performance using limited resources; or (ii) minimize its operations cost while guaranteeing a given quality of service. When the underlying optimization problem is NP-hard, metaheuristics are required to solve large-scale instances in reasonable computing times. Simheuristics extend metaheuristics by adding a simulation layer that allows the optimization component to deal with scenarios under uncertainty. This paper reviews both initial as well as recent applications of simheuristics, mainly in the area of logistics and transportation. The paper also discusses current trends and open research lines in this field.

[1]  Angel A. Juan,et al.  A BRILS metaheuristic for non-smooth flow-shop problems with failure-risk costs , 2016, Expert Syst. Appl..

[2]  Huashuai Qu,et al.  Simulation optimization: A tutorial overview and recent developments in gradient-based methods , 2014, Proceedings of the Winter Simulation Conference 2014.

[3]  J. P. Kelly,et al.  New advances for wedding optimization and simulation , 1999, WSC'99. 1999 Winter Simulation Conference Proceedings. 'Simulation - A Bridge to the Future' (Cat. No.99CH37038).

[4]  Fred W. Glover,et al.  Simulation-based optimization: practical introduction to simulation optimization , 2003, WSC '03.

[5]  Shane G. Henderson,et al.  An introduction to simulation optimization , 2015, 2015 Winter Simulation Conference (WSC).

[6]  Angel A. Juan,et al.  A simheuristic algorithm for solving the permutation flow shop problem with stochastic processing times , 2014, Simul. Model. Pract. Theory.

[7]  Juan José Ramos,et al.  A simheuristic algorithm for solving the arc-routing problem with stochastic demands , 2018, J. Simulation.

[8]  Angel A. Juan,et al.  Development and assessment of the SHARP and RandSHARP algorithms for the arc routing problem , 2012, AI Commun..

[9]  Laura Calvet,et al.  Learnheuristics: hybridizing metaheuristics with machine learning for optimization with dynamic inputs , 2017 .

[10]  Angel A. Juan,et al.  A simulation-optimization approach to deploy Internet services in large-scale systems with user-provided resources , 2014, Simul..

[11]  Angel A. Juan,et al.  A variable neighborhood search simheuristic for project portfolio selection under uncertainty , 2020, J. Heuristics.

[12]  Michael C. Fu,et al.  Optimization for Simulation: Theory vs. Practice , 2002 .

[13]  Laura Calvet,et al.  Waste collection under uncertainty: a simheuristic based on variable neighbourhood search , 2017 .

[14]  Sigrún Andradóttir,et al.  Chapter 20 An Overview of Simulation Optimization via Random Search , 2006, Simulation.

[15]  Angel A. Juan,et al.  Using safety stocks and simulation to solve the vehicle routing problem with stochastic demands , 2011 .

[16]  Angel A. Juan,et al.  A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems , 2015 .

[17]  J. P. Kelly,et al.  New advances and applications of combining simulation and optimization , 1996, Proceedings Winter Simulation Conference.

[18]  Averill M. Law,et al.  Simulation optimization: simulation-based optimization , 2002, WSC '02.

[19]  Fred W. Glover,et al.  Simulation optimization: a review, new developments, and applications , 2005, Proceedings of the Winter Simulation Conference, 2005..

[20]  Bernardo Almada-Lobo,et al.  Hybrid simulation-optimization methods: A taxonomy and discussion , 2014, Simul. Model. Pract. Theory.

[21]  Angel A. Juan,et al.  A simheuristic algorithm for the Single-Period Stochastic Inventory-Routing Problem with stock-outs , 2014, Simul. Model. Pract. Theory.

[22]  Angel A. Juan,et al.  Supporting multi-depot and stochastic waste collection management in clustered urban areas via simulation–optimization , 2017, J. Simulation.

[23]  Angel A. Juan,et al.  Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic , 2017, J. Oper. Res. Soc..

[24]  Javier Faulin,et al.  Using parallel & distributed computing for real-time solving of vehicle routing problems with stochastic demands , 2011, Annals of Operations Research.

[25]  Daniele Ferone,et al.  A biased-randomized simheuristic for the distributed assembly permutation flowshop problem with stochastic processing times , 2017, Simul. Model. Pract. Theory.

[26]  Angel A. Juan,et al.  A variable neighborhood search simheuristic for the multiperiod inventory routing problem with stochastic demands , 2020, Int. Trans. Oper. Res..