| Title |
A production planning model considering uncertain demand using two-stage stochastic programming in a fresh vegetable supply chain context
|
|---|---|
| Published in |
SpringerPlus, June 2016
|
| DOI | 10.1186/s40064-016-2556-z |
| Pubmed ID | |
| Authors |
Jordi Mateo, Lluis M. Pla, Francesc Solsona, Adela Pagès |
| Abstract |
Production planning models are achieving more interest for being used in the primary sector of the economy. The proposed model relies on the formulation of a location model representing a set of farms susceptible of being selected by a grocery shop brand to supply local fresh products under seasonal contracts. The main aim is to minimize overall procurement costs and meet future demand. This kind of problem is rather common in fresh vegetable supply chains where producers are located in proximity either to processing plants or retailers. The proposed two-stage stochastic model determines which suppliers should be selected for production contracts to ensure high quality products and minimal time from farm-to-table. Moreover, Lagrangian relaxation and parallel computing algorithms are proposed to solve these instances efficiently in a reasonable computational time. The results obtained show computational gains from our algorithmic proposals in front of the usage of plain CPLEX solver. Furthermore, the results ensure the competitive advantages of using the proposed model by purchase managers in the fresh vegetables industry. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Unknown | 49 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 30% |
| Student > Master | 5 | 10% |
| Lecturer | 3 | 6% |
| Student > Doctoral Student | 3 | 6% |
| Student > Bachelor | 2 | 4% |
| Other | 10 | 20% |
| Unknown | 12 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 18 | 36% |
| Business, Management and Accounting | 4 | 8% |
| Mathematics | 2 | 4% |
| Computer Science | 2 | 4% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 6 | 12% |
| Unknown | 17 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 July 2016.
All research outputs
#15,380,162
of 22,880,691 outputs
Outputs from SpringerPlus
#935
of 1,851 outputs
Outputs of similar age
#223,119
of 352,775 outputs
Outputs of similar age from SpringerPlus
#124
of 230 outputs
Altmetric has tracked 22,880,691 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,851 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 352,775 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 230 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.