### Abstract

Most of the research on integrated inventory and routing problems ignores the case when products are perishable. However, considering the integrated problem with perishable goods is crucial since any discrepancy between the routing and inventory cost can double down the risk of higher obsolescence costs due to the limited shelf-life of the products. In this paper, we consider a distribution problem involving a depot, a set of customers and a homogeneous fleet of capacitated vehicles. Perishable goods are transported from the depot to customers in such a way that out-of-stock situations never occur. The objective is to simultaneously determine the inventory and routing decisions over a given time horizon such that total transportation cost is minimized. We present a new “arc-based formulation” for the problem which is deemed more suitable for our new tabu search based approach for solving the problem. We perform a thorough sensitivity analysis for each of the tabu search parameters individually and use the obtained gaps to fine-tune the parameter values that are used in solving larger sized instances of the problem. We solve different sizes of randomly generated instances and compare the results obtained using the tabu search algorithm to those obtained by solving the problem using CPLEX and a recently published column generation algorithm. Our computational experiments demonstrate that the tabu search algorithm is capable of obtaining a near-optimal solution in less computational time than the time required to solve the problem to optimality using CPLEX, and outperforms the column generation algorithm for solving the “path flow formulation” of the problem in terms of solution quality in almost all of the considered instances.

Original language | English (US) |
---|---|

Pages (from-to) | 373-398 |

Number of pages | 26 |

Journal | Annals of Operations Research |

Volume | 242 |

Issue number | 2 |

DOIs | |

State | Published - Jul 1 2016 |

### Fingerprint

### Keywords

- Integer programming
- Inventory-routing
- Perishable goods
- Tabu search

### ASJC Scopus subject areas

- Decision Sciences(all)
- Management Science and Operations Research

### Cite this

*Annals of Operations Research*,

*242*(2), 373-398. https://doi.org/10.1007/s10479-014-1640-4

**A hybrid tabu search based heuristic for the periodic distribution inventory problem with perishable goods.** / Diabat, Ali; Abdallah, Tarek; Le, Tung.

Research output: Contribution to journal › Article

*Annals of Operations Research*, vol. 242, no. 2, pp. 373-398. https://doi.org/10.1007/s10479-014-1640-4

}

TY - JOUR

T1 - A hybrid tabu search based heuristic for the periodic distribution inventory problem with perishable goods

AU - Diabat, Ali

AU - Abdallah, Tarek

AU - Le, Tung

PY - 2016/7/1

Y1 - 2016/7/1

N2 - Most of the research on integrated inventory and routing problems ignores the case when products are perishable. However, considering the integrated problem with perishable goods is crucial since any discrepancy between the routing and inventory cost can double down the risk of higher obsolescence costs due to the limited shelf-life of the products. In this paper, we consider a distribution problem involving a depot, a set of customers and a homogeneous fleet of capacitated vehicles. Perishable goods are transported from the depot to customers in such a way that out-of-stock situations never occur. The objective is to simultaneously determine the inventory and routing decisions over a given time horizon such that total transportation cost is minimized. We present a new “arc-based formulation” for the problem which is deemed more suitable for our new tabu search based approach for solving the problem. We perform a thorough sensitivity analysis for each of the tabu search parameters individually and use the obtained gaps to fine-tune the parameter values that are used in solving larger sized instances of the problem. We solve different sizes of randomly generated instances and compare the results obtained using the tabu search algorithm to those obtained by solving the problem using CPLEX and a recently published column generation algorithm. Our computational experiments demonstrate that the tabu search algorithm is capable of obtaining a near-optimal solution in less computational time than the time required to solve the problem to optimality using CPLEX, and outperforms the column generation algorithm for solving the “path flow formulation” of the problem in terms of solution quality in almost all of the considered instances.

AB - Most of the research on integrated inventory and routing problems ignores the case when products are perishable. However, considering the integrated problem with perishable goods is crucial since any discrepancy between the routing and inventory cost can double down the risk of higher obsolescence costs due to the limited shelf-life of the products. In this paper, we consider a distribution problem involving a depot, a set of customers and a homogeneous fleet of capacitated vehicles. Perishable goods are transported from the depot to customers in such a way that out-of-stock situations never occur. The objective is to simultaneously determine the inventory and routing decisions over a given time horizon such that total transportation cost is minimized. We present a new “arc-based formulation” for the problem which is deemed more suitable for our new tabu search based approach for solving the problem. We perform a thorough sensitivity analysis for each of the tabu search parameters individually and use the obtained gaps to fine-tune the parameter values that are used in solving larger sized instances of the problem. We solve different sizes of randomly generated instances and compare the results obtained using the tabu search algorithm to those obtained by solving the problem using CPLEX and a recently published column generation algorithm. Our computational experiments demonstrate that the tabu search algorithm is capable of obtaining a near-optimal solution in less computational time than the time required to solve the problem to optimality using CPLEX, and outperforms the column generation algorithm for solving the “path flow formulation” of the problem in terms of solution quality in almost all of the considered instances.

KW - Integer programming

KW - Inventory-routing

KW - Perishable goods

KW - Tabu search

UR - http://www.scopus.com/inward/record.url?scp=84901868760&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84901868760&partnerID=8YFLogxK

U2 - 10.1007/s10479-014-1640-4

DO - 10.1007/s10479-014-1640-4

M3 - Article

AN - SCOPUS:84901868760

VL - 242

SP - 373

EP - 398

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

IS - 2

ER -