A multi-objective sustainable hub location-scheduling problem for perishable food supply chain

Musavi, MirMohammad; Bozorgi-Amiri, Ali

doi:10.1016/j.cie.2017.07.039

Cited by 170 publications

(87 citation statements)

References 49 publications

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“…Wu et al [13] proposed a multiperiod location model with transportation economies of scale that distributes a single perishable product and formulated the problem as a mixed integer nonlinear programming model. Musavi and Bozorgi-Amiri [14] present a novel sustainable hub locationvehicle scheduling model considering responsiveness and environmental impacts and propose an adopted nondominated sorting genetic algorithm-II (NSGA-II) metaheuristic approach to solve problems. Rezaei-Malek et al [15] propose a multiobjective model to design a disaster relief logistics hub location considering the lifetime of perishable products by adjusting certain time windows and consider the inherent uncertainty of input data.…”

Section: Scientific Programmingmentioning

confidence: 99%

“…Constraints (13) are the distribution center inventory constraints, and they enforce that the storage of the total fresh product does not exceed the maximum inventory capacity. Constraint (14) represents the number of new distribution center constraints. Constraint (15) ensures that each customer has only one candidate distribution center to deliver to him or her.…”

Section: Location Mathematical Model Under Determinatementioning

confidence: 99%

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Location Model for Distribution Centers for Fulfilling Electronic Orders of Fresh Foods under Uncertain Demand

Zhang

Xiong

et al. 2017

Scientific Programming

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The problem of locating distribution centers for delivering fresh food as a part of electronic commerce is a strategic decision problem for enterprises. This paper establishes a model for locating distribution centers that considers the uncertainty of customer demands for fresh goods in terms of time-sensitiveness and freshness. Based on the methodology of robust optimization in dealing with uncertain problems, this paper optimizes the location model in discrete demand probabilistic scenarios. In this paper, an improved fruit fly optimization algorithm is proposed to solve the distribution center location problem. An example is given to show that the proposed model and algorithm are robust and can effectively handle the complications caused by uncertain demand. The model proposed in this paper proves valuable both theoretically and practically in the selection of locations of distribution centers.

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Section: Scientific Programmingmentioning

confidence: 99%

Section: Location Mathematical Model Under Determinatementioning

confidence: 99%

Location Model for Distribution Centers for Fulfilling Electronic Orders of Fresh Foods under Uncertain Demand

Zhang

Xiong

et al. 2017

Scientific Programming

View full text Add to dashboard Cite

show abstract

“…In addition, unlike other products, their quality decreases continuously during the activities of the supply chain. Therefore, the process of dealing with food supply chain networks is complicated, with respect to other types of products that flow in this type of networks [1]. These products are easily affected by environmental factors and rot in the process of circulation and flow through the supply chain [2].…”

Section: Introductionmentioning

confidence: 99%

“…In addition to transport costs and response capacity in the optimization of a logistics system, the sustainable characteristics of the network must also be considered [1]. The importance of the environment is an issue that has been gaining strength for years in global production schemes.…”

Section: Introductionmentioning

confidence: 99%

Vehicles Allocation for Fruit Distribution Considering CO2 Emissions and Decisions on Subcontracting

2018

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An important problem in rural-area supply chains is how to transport the harvested fruit to urban areas. Low-and medium-capacity vehicles are used in Colombia to carry out this activity. Operating them comes with an inherent cost and generates carbon emissions. Normally, minimizing operating costs and minimizing carbon emissions are conflicting objectives to allocate such vehicles efficiently in any of the supply chain echelons. We designed a multi-objective mixed-integer programming model to address this problem and solved it via the ε-constraint method. It includes decisions mainly about quantities of fruit to transport and store, types of vehicles to allocate according to their capacities, CO 2 emission levels of these vehicles, and subcontracting on the collection process. The main results show two schedules for allocating the vehicles, showing minimum and maximum CO 2 emissions. Minimum CO 2 emissions scheme require subcontracting and the maximum CO 2 scheme does not. Then, a Pareto frontier shows that CO 2 emissions level are inversely proportional to total management cost for different scenarios in which fruit supply was modified.

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“…The SC of products and services tends to be complex and difficult to manage, especially when they involve perishable goods [3], and these are focused on rational planning, better communication…”

Section: Introductionmentioning

confidence: 99%

Impact of Infrastructure and Production Processes on Rioja Wine Supply Chain Performance

et al. 2018

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This paper presents a structural equation model for analyzing the relationship between four latent variables: infrastructure, production processes, transport benefits, and economic benefits within the supply chain for wine from La Rioja, Spain, by incorporating 12 observed variables. The model proposes six hypothesis that were tested using information gathered from 64 surveys completed by managers of several wineries in the region. The WarpPLS v.5 ® software (Version 5.0, Script Warp Systems, Laredo, TX, USA) was used to execute the model and analyze the direct, indirect, and total effects among latent variables. The results show that the control of production processes is a direct source of economic and transport benefits because of its higher explanatory power of those variables. Similarly, infrastructure is a direct source of transport and production benefits, and some of them are given indirectly. In addition, infrastructure does not have a direct effect on economic benefits; however, there were indirect effects given through production process and transport benefits. Infrastructure is a very important variable because of its influence in the final performance, but also because of its high environmental impact. Finally, economic benefits were explained in 43.8%, 19.1% belonging to production process, 21.1% coming from transport benefits, and 3.7% from infrastructure.

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A multi-objective sustainable hub location-scheduling problem for perishable food supply chain

Cited by 170 publications

References 49 publications

Location Model for Distribution Centers for Fulfilling Electronic Orders of Fresh Foods under Uncertain Demand

Location Model for Distribution Centers for Fulfilling Electronic Orders of Fresh Foods under Uncertain Demand

Vehicles Allocation for Fruit Distribution Considering CO2 Emissions and Decisions on Subcontracting

Impact of Infrastructure and Production Processes on Rioja Wine Supply Chain Performance

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