Resolving forward-reverse logistics multi-period model using evolutionary algorithms

Kumar, Vikas; Brady, Malcolm; Garza‐Reyes, Jose Arturo; Simpson, M.

doi:10.1016/j.ijpe.2016.04.026

Cited by 61 publications

(31 citation statements)

References 74 publications

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“…An exhaustive search can be inappropriate for large instances of this problem. Thus, genetic algorithms play an important role in solving complex mathematical problems in operations research (Kumar, Kumar, Brady, Garza-Reyes & Simpson, 2017;Diabat & Deskoores, 2016). Over the years, a wide range of industrial problems have been addressed through the application of a number of algorithms such as Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization Algorithms, and Artificial…”

Section: Methodsmentioning

confidence: 99%

Decision policy scenarios for just-in-sequence (JIS) deliveries

Cedillo-Campos¹,

Ruelas²,

Lizárraga-Lizárraga³

et al. 2017

JIEM

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Abstract:Purpose: The Just-in-Sequence (JIS) approach is evidencing advantages when controlling costs due to product variety management, and reducing the risk of disruption in sourcing, manufacturing companies and third-party logistics (3PL). This has increased its implementation in the manufacturing industry, especially in highly customized sectors such as the automotive industry. However, despite the growing interest from manufacturers, scholarly research focused on JIS still remains limited. In this context, little has been done to study the effect of JIS on the fluidity of supply chains and processes of logistics suppliers as well as providing them with a decision making tool to optimise the sequencing of their deliveries. Therefore, the aim of this paper is to propose a genetic algorithm to evaluate different decision policy scenarios to reduce risks of supply disruptions at assembly line of finished goods. Consequently, the proposed algorithm considers a periodic review of the inventory that assumes a steady demand and short response times is developed and applied.-581-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.2090Design/methodology/approach: Based on a literature review and real-life information, an abductive reasoning was performed and a case study application of the proposed genetic algorithm conducted in the automotive industry. Findings:The results obtained from the case study indicate that the proposed genetic algorithm offers a reliable solution when facing variability in safety stocks that operate under assumptions such as: i) fixed costs; ii) high inventory turnover; iii) scarce previous information concerning material requirements; and iv) replenishment services as core business value. Although the results are based on an automotive industry case study, they are equally applicable to other assembly supply chains.Originality/value: This paper is of interest to practitioners and academicians alike as it complements and supports the very limited scholarly research on JIS by providing manufacturers and 3PL suppliers competing in mass customized industries and markets, a decision support system to help decision making. Implications for the design of modern assembly supply chains are also exposed and future research streams presented.

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Section: Methodsmentioning

confidence: 99%

Decision policy scenarios for just-in-sequence (JIS) deliveries

Cedillo-Campos¹,

Ruelas²,

Lizárraga-Lizárraga³

et al. 2017

JIEM

Self Cite

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show abstract

“…The decision variables referred to include facility location, capacity, and customer allocation [49,50]. The optimisation objectives (and constraints) include total of costs, reliability, customer service level, responsive time to customer, and CO 2 emissions [49,51]. The methods to solve the MOO model generally consist of exact algorithm (e.g., TOPSIS, utility theory and minimax method), heuristics algorithm (e.g., hill climbing method), and metaheuristics algorithm (e.g., particle swarm algorithm, Current Paper √ √ √ (Network optimisation) * : refers to the paper in which the concepts related to items B are mentioned but not clarified.…”

Section: Moo Related To Cflp In Logisticsmentioning

confidence: 99%

Capacitated Facility Location and Allocation with Uncertain Demand for Tourism Logistics: A Multiobjective Optimisation Approach

Zhi-yang

et al. 2019

Mathematical Problems in Engineering

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The paper develops a Multiobjective Optimisation (MOO) model for addressing Capacitated Facility Location Problem (CFLP) in tourism logistics, where two objectives are total of cost and customer service level. Nondominated Sorting Genetic Algorithm II (NSGA II) is used to solve the model. The illustrative case with imaginary data demonstrates that the model can figure out the location of the nodes of tourism logistics network and allocation of these sites, while the total of cost is reduced by up to 56.75% and customer service level is increased by an average of 105%. The distinction of this study compared to the current papers is that our model incorporates both items A and B to the subject matter of tourism logistics, where items A refer to tourism-related products and items B involve personal goods of tourists. The model established is limited with one assumption and one limitation which are associated with Vehicle Routing Problem (VRP) and the boundary of tourism logistics activity. Therefore, further research for the elimination of these limits is recommended.

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“…Ten treatment options can be identified in the defective products' final disposal process: repackage, repair, disassembly, reconfiguration, remanufacturing, upgrade/modernization, recycling, donation to charitable purposes, sales on another market, or delivery to a landfill [31]. Each option (except delivery to a landfill) ends with a repeated inspection of the products or material collected within the final disposal process.…”

Section: Management Of Defective Products -Treatment Optionsmentioning

confidence: 99%

Environmental Approach to Managing Defective Products and Waste in the Household Appliances Industry

Starostka-Patyk¹

2019

Pol. J. Environ. Stud.

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The paper describes solutions that might have a huge environmental impact on the management of defective products and waste. It presents briefly the concepts of sustainable development, ecological design, closing material loops and the treatment options used to recover the value from defective products and waste, turning them into secondary raw materials. The Polish household appliances (HA) industry case is presented, as it is one of the biggest industries in Poland as well as dynamically developing. The research points out the options to manage HA defective products and waste, highlights the practices at this field of HA manufacturing enterprises, and creates the directions to be followed by the companies to become more environmentally focused, especially by designing their products with regard to ecological issues, following product life cycles, recovering the value from them, reusing materials in closed loops and finally by these elements generating less defective products and waste to not harm the natural environment.

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Resolving forward-reverse logistics multi-period model using evolutionary algorithms

Cited by 61 publications

References 74 publications

Decision policy scenarios for just-in-sequence (JIS) deliveries

Decision policy scenarios for just-in-sequence (JIS) deliveries

Capacitated Facility Location and Allocation with Uncertain Demand for Tourism Logistics: A Multiobjective Optimisation Approach

Environmental Approach to Managing Defective Products and Waste in the Household Appliances Industry

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