Systems and methods for enhancing harvest yield
Systems and methods are provided for allocating resources in harvest operations involving multiple fields and multiple pickers. One example computer-implemented method includes retrieving data specific to a harvest project and, for each of multiple stages for a site of the harvest project, determining, via a decision service, multiple potential allocations of the multiple pickers to fields of the site based on the retrieved data and one or more applicable constraints, advancing one or more of the potential allocations based on a determined parameter, and imposing at least one constraint consistent with ones of the one or more advanced potential allocations. The method then includes determining, via the decision service, at least one allocation of the multiple pickers to the multiple fields based on the retrieved data and one or more applicable constraints, compiling and storing a harvest plan for the harvest project, and implementing the harvest plan.
1. A computer-implemented method for use in allocating resources in harvest operations involving multiple fields and multiple pickers, the method comprising:
(a) retrieving, by a platform computing device, from a data structure, data specific to a harvest project, the harvest project including at least one site, the at least one site including multiple fields, and wherein the data includes identifying data for the multiple fields, location data for the multiple fields and multiple pickers, and moisture content(s) for one or more crops included in the multiple fields;
(b) for each of at least one individual site stage, for each site of the at least one site, where the at least one individual site stage is applicable to each site of the at least one site:
determining, by the platform computing device in communication with the data structure, via a decision service, multiple potential allocations of the multiple pickers to the multiple fields of the at least one site based on the retrieved data and one or more applicable constraints;
determining, by the platform computing device, a first parameter of the multiple potential allocations;
advancing, by the platform computing device, one or more of the multiple potential allocations, based on the determined first parameter; and
imposing, by the platform computing device, at least one first constraint consistent with ones of the advanced one or more of the multiple potential allocations; and then
(c) further determining, by the platform computing device in communication with the data structure, via the decision service, at least one allocation of the multiple pickers to the multiple fields based on the retrieved data and the at least one first constraint;
(d) for at least one all-site stage and for each site of the at least one site, where the at least one all-site stage is applicable to each site of the at least one site:
determining, by the platform computing device, a second parameter of the at least one allocation of the multiple pickers for each site of the at least one site;
advancing, by the platform computing device, one or more of the at least one allocation, based on the determined second parameter of the at least one allocation; and
imposing, by the platform computing device, at least one second constraint consistent with the advanced one or more of the at least one allocation;
(e) determining, by the platform computing device, via the decision service, at least one final allocation for the at least one site, based on the retrieved data and the at least one second constraint;
(f) storing, by the platform computing device, in memory associated with the platform computing device, a harvest plan for the harvest project, based on the at least one final allocation of the multiple pickers to the multiple fields; and
(g) sending, by the platform computing device, the harvest plan to the multiple pickers, which causes the multiple pickers to travel to the multiple fields and to automatically harvest, based on GPS included in the multiple pickers, one or more crops in the multiple fields, consistent with the harvest plan.
2. The computer-implemented method of claim 1 , wherein the at least one individual site stage includes multiple individual site stages.
3. The computer-implemented method of claim 2 , wherein the determined first parameter includes at least one of a number of fake pickers included in the multiple potential allocations, a batch duration of the multiple potential allocations, a timing of harvest associated with ones of the multiple fields of the multiple potential allocations; and an expected yield of the multiple potential allocations.
4. The computer-implemented method of claim 1 , wherein the imposed at least one first constraint includes: ones of the multiple pickers assigned to ones of the multiple fields, a limit on batch durations of the multiple potential allocations, a precedence associated with ones of the multiple fields within the at least one site, and/or a lower bound on a yield of the multiple potential allocations.
5. The computer-implemented method of claim 1 , wherein the imposed at least one first constraint includes at least one or more of the following:
∑
∀
b
∈
batches
SAPBatchDuration
b
≥
∅
where
∅
is
a
parameter
;
∑
f
∈
fieids
,
pushDays
f
=
0
,
t
∈
harvestTime
f
,
t
<
M
p
f
-
p
u
s
h
D
a
y
s
f
M
P
B
i
n
f
≤
{
f
|
f
∈
fields
:
pushDays
f
=
0
}
;
and
/
or
realVolDiffPos
hl
≥
supply
l
h
-
∑
p
∑
f
∑
t
yieldMoisture
f
t
×
acres
f
×
dailyHarvestHrs
×
pickerSpeed
×
harvestFraction
pft
∀
h
∈
hybrids
,
l
∈
demandLevels
.
6. The computer-implemented method of claim 1 , further comprising:
determining, by the platform computing device, a third parameter of the at least one final allocation for each site of the at least one site; and
advancing, by the platform computing device, one or more of the at least one final allocation, based on the determined third parameter of the at least one final allocation for each site of the at least one site; and
wherein storing the harvest plan for the harvest project is based on the advanced one or more of the at least one final allocation.
7. The computer-implemented method of claim 6 , wherein the determined second parameter of the at least one allocation of the multiple pickers for each site of the at least one site and/or the determined third parameter of the at least one final allocation for each site of the at least one site includes at least one of: a shortfall between an expected yield and a demand for the multiple potential allocations and a start time for batches included in the multiple potential allocations.
8. The computer-implemented method of claim 1 , wherein the imposed at least one first constraint includes a balance of supply and demand for the multiple potential allocations.
9. The computer-implemented method of claim 1 , wherein the multiple pickers include corn ear pickers and/or combines.
10. The computer-implemented method of claim 1 , wherein the decision service includes a mixed integer programming model based on an objective function and the one or more applicable constraints, and wherein the one or more applicable constraints are represented as linear inequalities.
11. The computer-implemented method of claim 1 , further comprising updating the data included in the data structure for a harvest interval, and then repeating steps (a) through (g) at one or more regular intervals.
12. The computer-implemented method of claim 1 , further comprising harvesting, by the multiple pickers, the one or more crops included in the multiple fields based at least in part on the harvest plan.
13. A non-transitory computer-readable storage medium including executable instructions for allocating resources in harvest operations involving multiple fields and multiple pickers, which when executed by at least one processor, cause the at least one processor to:
retrieve, from a data structure, data specific to a harvest project, the harvest project including multiple sites, and the multiple sites including multiple fields, and wherein the data includes identifying data for the multiple fields, location data for the multiple fields and multiple harvesting machines, and moisture content(s) for one or more crops included in the multiple fields;
for each of at least one individual site stage, for each site of the multiple sites, where the at least one individual site stage is applicable to each site of the multiple sites:
determine, via a decision service, multiple potential allocations of the multiple harvesting machines to the multiple fields based on the retrieved data and one or more applicable constraints;
determine a first parameter of the multiple potential allocations;
advance one or more of the multiple potential allocations, based on the determined first parameter; and
impose at least one first constraint consistent with ones of the advanced one or more of the multiple potential allocations; and then
further determine, via the decision service, at least one allocation of the multiple harvesting machines to the multiple fields based on the retrieved data and the at least one first constraint;
for at least one all-site stage and for all of the multiple sites, where the all-site stage is applicable to all of the multiple sites:
determine a second parameter of the at least one allocation of the multiple pickers for all of the multiple sites;
advance one or more of the at least one allocation, based on the determined second parameter of the at least one allocation for all of the multiple sites; and
impose at least one second constraint consistent among the advanced one or more of the at least one allocation;
determine, via the decision service, at least one final allocation for the multiple sites, based on the retrieved data and the at least one second constraint;
store, in memory associated with the at least one processor, a harvest plan for the harvest project, based on the at least one final allocation of the multiple harvesting machines to the multiple fields of the multiple sites; and
send the harvest plan to the multiple pickers, which causes the multiple pickers to travel to the multiple fields and to automatically harvest, based on GPS included in the multiple pickers, one or more crops in the multiple fields consistent with the harvest plan.
14. The non-transitory computer-readable storage medium of claim 13 , wherein the imposed at least one first constraint includes at least one or more of the following:
∑
∀
b
∈
batches
SAPBatchDuration
b
≥
∅
wherein Ø is a threshold parameter;
∑
f
∈
fieids
,
pushDays
f
=
0
,
t
∈
harvestTime
f
,
t
<
M
p
f
-
p
u
s
h
D
a
y
s
f
M
P
B
i
n
f
≤
{
f
|
f
∈
fields
:
pushDays
f
=
0
}
;
and
/
or
realVolDiffPos
hl
≥
supply
l
h
-
∑
p
∑
f
∑
t
yieldMoisture
f
t
×
acres
f
×
dailyHarvestHrs
×
pickerSpeed
×
harvestFraction
pft
∀
h
∈
hybrids
,
l
∈
demandLevels
.
15. A system for use in allocating resources in harvest operations involving multiple fields and multiple harvesting machines, the system comprising at least one computing device configured to:
retrieve, from a data structure, data specific to a harvest project, the harvest project including at least one site, the at least one site including multiple fields, and wherein the data includes identifying data for the multiple fields, location data for the multiple fields and multiple harvesting machines, and moisture content(s) for one or more crops included in the multiple fields;
for each of at least one individual site stage, for each site of the at least one site, where the at least one individual site stage is applicable to each site of the at least one site:
determine, via a decision service, multiple potential allocations of the multiple harvesting machines to the multiple fields of the at least one site based on the retrieved data and one or more applicable constraints;
determine a first parameter of the multiple potential allocations;
advance one or more of the multiple potential allocations, based on the determined first parameter; and
impose at least one first constraint consistent with ones of the advanced one or more of the multiple potential allocations; and then
further determine, via the decision service, at least one allocation of the multiple harvesting machines to the multiple fields based on the retrieved data and the at least one first constraint;
for at least one all-site stage and for each site of the at least one site, where the at least one all-site stage is applicable to each site of the at least one site:
determine a second parameter of the at least one allocation of the multiple harvesting machines for each site of the at least one site;
advance one or more of the at least one allocation, based on the determined second parameter of the at least one allocation; and
impose at least one second constraint consistent among the advanced one or more of the at least one allocation;
determine, via the decision service, at least one final allocation for the at least one site, based on the retrieved data and the at least one second constraint;
store, in memory associated with the computing device, a harvest plan for the harvest project, based on the at least one final allocation of the multiple harvesting machines to the multiple fields; and
send the harvest plan to the multiple harvesting machines, which causes the multiple harvesting machines to travel to the multiple fields and to automatically harvest, based on GPS included in the multiple harvesting machines, one or more crops in the multiple fields consistent with the harvest plan.
16. The system of claim 15 , further comprising the multiple harvesting machines; and
wherein the multiple harvesting machines are configured, by the harvest plan, to harvest the one or more crops included in the multiple fields consistent with the harvest plan.
17. The non-transitory computer-readable storage medium of claim 13 , wherein the imposed at least one first constraint includes a balance of supply and demand for the multiple potential allocations for all of the multiple sites.
18. The non-transitory computer-readable storage medium of claim 13 , wherein the executable instructions, when executed by the at least one processor, further cause the at least one processor to:
determine a third parameter of the at least one final allocation for the multiple sites; and
advance one or more of the at least one final allocation, based on the determined third parameter of the at least one final allocation for the multiple sites; and
wherein the executable instructions when executed by at least one processor, cause the at least one processor, in storing the harvest plan, to store the harvest plan for the harvest project based on the advanced one or more of the at least one final allocation.
19. The non-transitory computer-readable storage medium of claim 18 , wherein the determined second parameter of the at least one allocation and/or the determined third parameter of the at least one final allocation includes at least one of: a shortfall between an expected yield and a demand for the multiple potential allocations for all of the multiple sites and a start time for batches included in the multiple potential allocations for all of the multiple sites.