A location-inventory supply chain network model using two heuristic algorithms for perishable products with fuzzy constraints

Dai, Zhuo; Aqlan, Faisal; Zheng, Xunhua; Gao, Kuo

doi:10.1016/j.cie.2018.04.007

Cited by 67 publications

(45 citation statements)

References 60 publications

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“…Raw material availability is considered as an important part in identifying safety stock level because unavailability of raw material will lead to unmet customer requirements. The steps below show how raw material availability was employed in this model;  Building set of membership functions to describe the statues of raw material availability as shown in figure (3).…”

Section: Raw Materials Availabilitymentioning

confidence: 99%

Development of Fuzzy Logic Approach to Optimize Safety Stock Level in Deteriorated Products/a Supply Chain Dairy Industries Case Study

Jamegh

Kassam²,

Sabih³

2019

QJES

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In today's complex environment, a high responding ability represents a core for each organization to survive in a competitive environment. To grip your position in intense competition market, the organization must design high efficiency inventory system that has the ability to respond to changes in demand and at the same time reduce holding cost of accommodation to the lowest possible value by controlling inventory drivers such as safety stock level (SS). The traditional approaches of safety stock are limited to deal with dynamic behavior of market. Advanced approaches based on soft computing allow the dynamic updating of SS level. In this paper, a highly advanced dynamic fuzzy logic (DFL) has been suggested as an innovation step to identify safety stock level in dairy industries with objective of minimizing total cost and meet with customer requirements. The proposed approach consists of three main steps firstly, identifying demand uncertainty conditions by applying fuzzy logic steps embedded by identifying dynamic (N) factor which represents the increasing level in demand in period time. Secondly, identifying of raw material availability conditions by applying fuzzy logic steps, and finally, identification of inventory on hand conditions by applying fuzzy logic steps. It is necessary to identify the level of SS dynamically in fuzzy logic as an output embedded with identifying of period specification concept which describes states of demand in a specific period in which the demand is high, medium, or low which leads to identify maximum values of universe of discourse of output (safety stock). Here Matlab program was used. The provided solution demonstrates the proposed model validity. There has been a significant reduction in safety stock level ranging from (7-98)% depending on product type and period specification with a reduction also in holding cost, while keeping the requirements fulfillment of customers demand

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Section: Raw Materials Availabilitymentioning

confidence: 99%

Development of Fuzzy Logic Approach to Optimize Safety Stock Level in Deteriorated Products/a Supply Chain Dairy Industries Case Study

Jamegh

Kassam²,

Sabih³

2019

QJES

View full text Add to dashboard Cite

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“…For example, location-inventory models are extended to consider difference inventory control strategies [33], uncertain or correlated demands [34,35], lateral transshipment [36], product attributes (e.g., perishable products, seasonal products, substitutable products, etc.) [37,38], and third-party logistics [39]. As the emergence of CLSCs, LIPs are also studied by considering reverse logistics.…”

Section: Literature Reviewmentioning

confidence: 99%

A Location-Inventory Problem in a Closed-Loop Supply Chain with Secondary Market Consideration

Guo

Zhang

et al. 2018

Sustainability

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To design sustainable supply chain systems in today's business environment, this paper studies a location-inventory problem in a closed-loop supply chain by considering the sales of new and used products in the primary and secondary markets, respectively. This problem is formulated as a mixed-integer nonlinear program to optimize facility location and inventory management decisions jointly, and the logistics flows between the two markets are modeled dynamically. To solve this problem efficiently, a new heuristic approach is also developed by introducing an effective adaptive mechanism into differential evolution. Finally, numerical experiments are presented to validate the solution approach and provide valuable managerial insight. This paper makes a meaningful contribution to the literature by incorporating the secondary market into the study of closed-loop supply chains, and practically, it is also greatly beneficial to improve the sustainability and efficiency of modern supply chains.

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“…The location inventory problem (LIP) is the integrated form of the first two problems, and they are first proposed by Daskin et al [7] and Shen et al [8]. LIPs have been extended with many business scenarios such as lateral transshipment [9], perishable products [10], correlated demands [11], disruption risk [12], and inventory control strategies [13], and most of those works are reviewed by Farahani et al [14]. Recently, LIPs are also studied by incorporating CLSCs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (9) is the vehicle capacity constraint which means that the total demand in a route cannot exceed the capacity of a vehicle. Constraint (10) means that vehicles can be assigned to a HDCC only if the HDCC has been built. Constraint (11) means that at least one vehicle will be assigned to a HDCC.…”

Section: Complexitymentioning

confidence: 99%

A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed‐Loop Supply Chain

Guo

Zhang

et al. 2018

Complexity

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Facility location, inventory management, and vehicle routing are three important decisions in supply chain management, and location-inventory-routing problems consider them jointly to improve the performance and efficiency of today’s supply chain networks. In this paper, we study a location-inventory-routing problem to minimize the total cost in a closed-loop supply chain that has forward and reverse logistics flows. First, we formulate this problem as a nonlinear integer programming model to optimize facility location, inventory control, and vehicle routing decisions simultaneously in such a system. Second, we develop a novel heuristic approach that incorporates simulated annealing into adaptive genetic algorithm to solve the model efficiently. Last, numerical analysis is presented to validate our solution approach, and it also provides meaningful managerial insight into how to improve the closed-loop supply chain under study.

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A location-inventory supply chain network model using two heuristic algorithms for perishable products with fuzzy constraints

Cited by 67 publications

References 60 publications

Development of Fuzzy Logic Approach to Optimize Safety Stock Level in Deteriorated Products/a Supply Chain Dairy Industries Case Study

Development of Fuzzy Logic Approach to Optimize Safety Stock Level in Deteriorated Products/a Supply Chain Dairy Industries Case Study

A Location-Inventory Problem in a Closed-Loop Supply Chain with Secondary Market Consideration

A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed‐Loop Supply Chain

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