Optimization Online


Recent Progress Using Matheuristics for Strategic Maritime Inventory Routing

Dimitri Papageorgiou(dimitri.j.papageorgiou***at***exxonmobil.com)
Myun-Seok Cheon(myun-seok.cheon***at***exxonmobil.com)
Stuart Harwood(stuart.m.harwood***at***exxonmobil.com)
Francisco Trespalacios(francisco.trespalacios***at***exxonmobil.com)
George Nemhauser(gnemhaus***at***isye.gatech.edu)

Abstract: This paper presents an extensive computational study of simple, but prominent matheuristics (i.e., heuristics that rely on mathematical programming models) to fi nd high quality ship schedules and inventory policies for a class of maritime inventory routing problems. Our computational experiments are performed on a set of the publicly available MIRPLib instances. This class of inventory routing problems has few constraints relative to some operational problems, but has long planning horizons, which make the time dimension challenging. We compare several variants of rolling horizon heuristics, K-opt heuristics, local branching, solution polishing, and hybrids thereof. Many of these matheuristics substantially outperform the commercial mixed-integer programming solvers CPLEX 12.6.2 and Gurobi 6.5 in their ability to quickly find high quality solutions. New best known incumbents are found for 26 out of 70 yet-to-be-proved-optimal instances and new best known bounds on 56 instances.

Keywords: deterministic inventory routing, matheuristics, maritime transportation, mixed-integer linear programming, time decomposition

Category 1: Applications -- OR and Management Sciences (Transportation )

Category 2: Combinatorial Optimization (Meta Heuristics )

Category 3: Integer Programming ((Mixed) Integer Linear Programming )

Citation: Book chapter in forthcoming Springer Volume: "Modelling, Computing and Data Handling Methodologies for Maritime Transportation."

Download: [PDF]

Entry Submitted: 12/29/2016
Entry Accepted: 12/29/2016
Entry Last Modified: 12/29/2016

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