An incremental approach using local-search heuristic for inventory routing problem in industrial gases

Singh, Tejinder; Arbogast, Jeffrey E.; Neagu, Nicoleta

doi:10.1016/j.compchemeng.2015.05.023

Cited by 29 publications

(12 citation statements)

References 29 publications

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“…The logistic ratio is the average cost to distribute a single unit of product and captures the long‐term impact of a short‐term planning given that it focuses on the efficiency of the process rather than on the short‐term (local) cost. This type of measure can be encountered in real‐life IRPs, especially in the distribution in the bulk gas industry (Benoist et al., ; Singh et al., ; Archetti et al., ).…”

Section: Problem Descriptionmentioning

confidence: 99%

“…() and Singh et al. () solved different IRPs by applying heuristic algorithms to real‐life distribution problems in the bulk gas industry. For other studies on applications and variants of the IRP, see the comprehensive reviews by Andersson et al.…”

Section: Introductionmentioning

confidence: 99%

“…The logistic ratio can be of great value in practical contexts, as it can better reflect the efficiency of the distribution process. Despite its practical motivation, only a few studies have dealt with this kind of objective function in the context of IRPs (Benoist et al., ; Singh et al., ; Archetti et al., ). The logistic ratio imposes challenges to integer programming formulations and exact methods, as it corresponds to a nonlinear function.…”

Section: Introductionmentioning

confidence: 99%

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Iterated local search and simulated annealing algorithms for the inventory routing problem

Álvarez

Munari

Morábito

2018

Int Trans Operational Res

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This paper addresses the inventory routing problem (IRP), which consists in defining the customer visit schedule, the delivery quantities, and the vehicle routing plan to meet the demands of a set of customers over a given time horizon. We consider the variant with a single item, a single supplier, multiple vehicles, and a finite multiperiod planning horizon, minimizing the sum of inventory and travel costs. In addition, we address an alternative objective function that minimizes the logistic ratio, defined as the total travel cost divided by the total quantity delivered to customers. This second objective function, while more realistic in some logistics settings, poses a challenge for integer programming models and exact methods because of its nonlinearity. To our knowledge, no heuristic method has been proposed to address this objective in the IRP variant addressed in this paper. To solve this problem with each of these objective functions, we propose effective metaheuristic algorithms based on iterated local search and simulated annealing. Computational experiments show that these algorithms provide reasonably high-quality solutions in relatively short running times for both objective functions when compared to other methods for well-known instances from the literature. Moreover, the algorithms produce new best solutions for some of these instances.

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Section: Problem Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Iterated local search and simulated annealing algorithms for the inventory routing problem

Álvarez

Munari

Morábito

2018

Int Trans Operational Res

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“…Nearly all of the analytical problems and algorithms in this area aimed at total cost minimization. However, service level is the most studied secondary objective [71][72][73][74][75][76]. Two of these studies aimed at enhancing the demand coverage by the maximization of the collected rewards from the visited demand nodes [73,75].…”

Section: Inventory Routing Problemsmentioning

confidence: 99%

“…Two of these studies aimed at enhancing the demand coverage by the maximization of the collected rewards from the visited demand nodes [73,75]. The minimum missed order is achieved in the proposed model by Singh et al [72], while another relevant study by Agra et al [77] focused on the optimization of backlogged demands to improve the service level. In another example of responsive service design, Chow and Nurumbetova [76] aimed at minimizing delays in a multi-objective basis.…”

Section: Inventory Routing Problemsmentioning

confidence: 99%

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Pourhejazy

Kwon

2016

Sustainability

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Abstract:The possibilities of applying Operations Research (O.R.) techniques in the design of real-world systems are vast. The optimization and design of the supply chain network (SCN) is one of the relevant topics that has directed the attention of many scholars. Sound decisions in this regard, including the proper selection of the facility's location, transportation modes and routes and inventory management policies, can noticeably improve the systems performance. Over 380 articles published between 2005 and 2016 in the ISI/Web of Science database have applied advanced O.R. techniques in SCN optimization studies. This paper offers a systematic review of these published contributions by focusing on two categories of O.R. approaches most recently applied for the design of SC systems: integrated mathematical modeling and simulation-optimization (S-O) frameworks. A taxonomy analysis of the mentioned approaches is presented based on the supply chain elements. A bibliometric analysis is also conducted to provide technical insights into the possible gaps in the field. Moreover, the relevant studies on SC sustainability are highlighted. The research results are supportive of the S-O frameworks as either an alternative approach or an effective solution method for the integrated problems. The research outcomes can provide researchers in the field with useful details of the integrated problems and S-O frameworks as the most recent O.R. methodologies in the field of SC optimization.

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Computational Intelligence and Combinatorial Optimization Problems in Transportation Science

Kritikos

Lappas

2020

Learning and Analytics in Intelligent Systems

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An incremental approach using local-search heuristic for inventory routing problem in industrial gases

Cited by 29 publications

References 29 publications

Iterated local search and simulated annealing algorithms for the inventory routing problem

Iterated local search and simulated annealing algorithms for the inventory routing problem

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Computational Intelligence and Combinatorial Optimization Problems in Transportation Science

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