Incorporating location and inventory decisions into a supply chain design problem with uncertain demands and lead times

Diabat, Ali; Dehghani, Ehsan; Jabbarzadeh, Armin

doi:10.1016/j.jmsy.2017.02.010

Cited by 71 publications

(28 citation statements)

References 59 publications

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“…Zhang and Unnikrishnan [13] presented a location-inventory model with uncertain demands, which is based on integer nonlinear programming and can be transformed to conic quadratic mixed-integer programming, and used CPLEX software solve this problem. Diabat et al [14] presented a joint location-inventory model based on uncertain demands and lead times, the use of which can determine not only the location and number of distribution centers but also the size, and adopted a hybrid algorithm to solve the presented model; this algorithm arose from simulated annealing and direct search. Vahdani et al [15] considered a model based on mixed-integer nonlinear programming for a location-inventory problem, which assumed that the demands of retailers are correlated, and presented two metaheuristic algorithms, including genetic algorithm and simulated annealing to solve this problem.…”

Section: Literature Reviewmentioning

confidence: 99%

“…By introducing auxiliary variables , for each and , is defined by constraint (14), and is defined by constraint (15). Now we, based on the above formulation, give conic quadratic mixed-integer programming model (CQMIP):…”

Section: − ( + + )mentioning

confidence: 99%

“…In order to get a better solution we strengthen the formulations (CQMIP) with cover inequalities, utilize the left side of inequality (14) to substitute , and then we receive the nonlinear 0-1 constraint knapsack result:…”

Section: Extended Cover Cutsmentioning

confidence: 99%

See 2 more Smart Citations

Combined Location-Inventory Optimization of Deteriorating Products Supply Chain Based on CQMIP under Stochastic Environment

Wang

Yin

2018

Mathematical Problems in Engineering

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The design and optimization of combined location-inventory model for deteriorating products are a main focus in supply chain management. There were many combined location-inventory design models in this field, but these models are under the assumptions of adequate capacity facilities, invariable lead time, unique product, and uncorrelated retailer's demands. These assumptions have a big gap in the practical situation. In this paper, we design a combined location-inventory model for deteriorating products under capacitated facilities, stochastic lead time, multiple products, and correlated retailers' stochastic demands assumptions. These constraints are near to actual supply chain circumstance. The problem is modeled as conic quadratic mix-integer programming (CQMIP) to minimize the total expected cost. We explain how to formulate these problems as conic quadratic mixed-integer problems, and in order to obtain better computational results we use extended cover cuts. Simultaneously we compare our method with the previous Lagrange methods; the result is that the new CQMIP method can get better solution.

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Section: Literature Reviewmentioning

confidence: 99%

Section: − ( + + )mentioning

confidence: 99%

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Combined Location-Inventory Optimization of Deteriorating Products Supply Chain Based on CQMIP under Stochastic Environment

Wang

Yin

2018

Mathematical Problems in Engineering

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“…Sadjadi et al (2016) used queue theory to determine positive and negative inventory levels in a three-level supply chain model. Similarly, queue theory was used by Diabat et al (2017) in determining expected reorder point, inventory and lost sale with uncertain demand and uncertain lead time.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi Echelon Location-Inventory Model with Lateral Transshipment

Gholamian

Nasri

2019

OSCM: An Int. Journal

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In this research, a supply chain system consisting producer, distribution centers and retailers is modeled by considering lateral transshipment between distribution centers and also using echelon-based inventory system instead of independent inventory system. The model is developed in the form of mixed integer non-linear programming (MINLP) to minimize the total location, transportation, and inventory costs of the system. The model was solved using conic programming approach and validity was examined by comparing the developed model with the basic model (i.e. the model without the contributions) in several instances with different sizes of distributors and retailers. The results represent superiority of the developed model in computational time and objective value especially in medium and large-scale problems.

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“…Demand, service process is independent process and follows an exponential distribution. It is assumed that always demand and supply balanced [12,13]. So that product is serviced in a stipulated time without extra cost [14].…”

Section: Introductionmentioning

confidence: 99%

Performance Measures of Online Warehouse Service System with Replenishment Policy

Saritha¹,

Mamatha²,

Reddy³

2019

JESA

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In this work, we studied an inventory model with a single-component preservation system and the replenishment schedule as decision variables. The system has characteristics with three distinct states. The productive items are maintained in the warehouse, the items are serviced on demand of the customers, any defective items are to be serviced if it serviceable or discarded. The system is monitored periodical intervals, and the warehouse system is maintained with frequent observations and inspections. Based on the request of the customer the products are serviced. If any defective product is serviced then the customer has the right to the returned product with a new item or amount paid. The defective items that are returned from the customers re-entered into the service system after repair or discarded as scrap. The key intention of the paper is to minimize the optimization of cost, minimal time service, and effective stock of the warehouse. The produced results show that effective improvement with existing metrics. Finally, we formulated an inventory model for the stochastic optimal performance measures of various parameters.

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Incorporating location and inventory decisions into a supply chain design problem with uncertain demands and lead times

Cited by 71 publications

References 59 publications

Combined Location-Inventory Optimization of Deteriorating Products Supply Chain Based on CQMIP under Stochastic Environment

Combined Location-Inventory Optimization of Deteriorating Products Supply Chain Based on CQMIP under Stochastic Environment

A Multi Echelon Location-Inventory Model with Lateral Transshipment

Performance Measures of Online Warehouse Service System with Replenishment Policy

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