Group managing system for elevator cars

• US 5,780,789 A
• Filed: 06/25/1997
• Issued: 07/14/1998
• Est. Priority Date: 07/21/1995
• Status: Expired due to Fees

• Current Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Inventors: Tsuji, Shintaro
• Primary Examiner(s): NAPPI, ROBERT E
• Application Number:
  US08/882,226
• Time in Patent Office: 384 Days
• Field of Search: 187/380, 187/382, 187/387, 187/391, 187/393, 395/901, 395/13
• US Class Current: 187/382
• CPC Class Codes: B66B 1/2458 For elevator systems with multiple shafts and a single car per shaft
• CPC Class Codes: B66B 2201/102 Up or down call input
• CPC Class Codes: B66B 2201/211 Waiting time, i.e. response time
• CPC Class Codes: B66B 2201/216 Energy consumption
• CPC Class Codes: B66B 2201/401 by time of the day
• CPC Class Codes: B66B 2201/403 by real-time traffic data
• CPC Class Codes: Y10S 700/90 Special robot structural element

Abstract

A system for group managing plural elevator cars according to a group management algorithm including plural parameters includes a seeking apparatus for seeking the optimum parameter set, the optimum set being taken from combinations of parameter values given to the group management algorithm. Some new sets are produced by crossover or mutation in the operation of the system. Excellent sets are accumulated in a memory using additional registrations in which excellent sets are additionally stored in the memory and deletions in which impaired sets are deleted from the memory. The optimum set is selected from the accumulated sets, so that the system can efficiently seek the optimum set.

Claims

1. A system for group managing a plurality of elevator cars according to a group management algorithm including a plurality of parameters, said system including:

a group management apparatus for implementing a group management algorithm for controlling a plurality of elevators and for outputting a seeking condition signal, the seeking condition signal including at least one of;

traffic flow specification data, elevator car specification data, and seeking command data;

a seeking apparatus for seeking an optimum set from a plurality of sets, said seeking apparatus comprising;

memorizing means for storing a plurality of sets and group management performance data for each set, each set including a plurality of parameter values to be input into the group management algorithm, the group management performance data including information regarding a waiting time of an elevator user, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

producing means for selecting one or plural sets as a parent or parents from said memorizing means and for producing one or plural new sets inheriting part of the characteristics of the parent or parents;

estimating means for estimating a result of execution of the group management algorithm using each new set in response to the seeking condition signal, the result of executing being group management performance data for each new set, the group management performance data including information regarding a waiting time of an elevator user, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management performance algorithm using the respective sets;

selecting means for improving the plurality of sets stored in said memorizing means through both of addition of the new sets to said memorizing means based on the group management performance data for each new set and deletion of impaired sets from said memorizing means based on the group management performance data of each impaired set, the addition of the new sets including storing the group management performance data corresponding to each new set with each new set stored in said memorizing means, the deletion of the impaired sets including deleting the group management performance data corresponding to each impaired set with each set deleted from said memorizing means; and

extracting means for extracting an optimum set based on the group management performance data from among the plurality of sets stored in said memorizing means.

2. A system as set forth in claim 1, wherein said producing means includes:

numerical value exchanging means for producing two new sets by exchanging numerical value portions between two sets which are selected from said memorizing means;

new value replacing means for producing one new set by replacing a part of a plurality of parameter values of one set selected from said memorizing means with new numerical values generated in a random manner; and

production method selecting means for selecting between exchanging of numerical values and replacing of new values according to a probability.

3. A system as set forth in claim 1, wherein said producing means includes:

parent selecting means for selecting one or plural sets from said memorizing means;

parameter selecting means for selecting, in conjunction with the one or two sets, parameters by which exchanging of numerical values or replacing of new values is performed;

numerical value exchanging means for producing two new sets by exchanging between two sets which are selected by said parent selecting means a portion of values of the parameters which are selected by said parameter selecting means;

new value replacing means for producing one new set by replacing parameter values, selected by said parameter selecting means, of one set selected by said parent selecting means with new numerical values generated in a random manner; and

production method selecting means for selecting between exchanging of numerical values and replacing of new values according to a probability.

4. A system as set forth in claim 3, wherein said parent selecting means performs parent selections based on parent selection reference information for raising production probability of excellent new sets.

5. A system as set forth in claim 4, wherein the parent selection reference information is the distance between sets and wherein said parent selecting means computes the distance between sets and randomly selects from said memorizing means a pair of sets at which the distance between sets satisfies a certain condition.

6. A system as set forth in claim 4, wherein the parent selection reference information includes the group management performance data stored with each set in said memorizing means and wherein said parent selecting means weights a selection probability of each set according to the group management performance data and thereby randomly selects one or two sets from said memorizing means.

7. A system as set forth in claim 4, wherein the parent selection reference information is the number of similar sets and wherein said parent selecting means computes the number of similar sets for every set, weights a selection probability of each set according to the number of similar sets, and thereby randomly selects one or two sets from said memorizing means.

8. A system as set forth in claim 3, further comprising modifying means for modifying parent selection conditions in accordance with proceeding circumstances of seeking.

9. A system as set forth in claim 3, wherein said parameter selection means selects the parameter, based on parameter selection reference information for raising the probability of producing excellent new sets.

10. A system as set forth in claim 9, wherein the parameter selection reference information is the difference of the two parameter values to be exchanged between the two sets and wherein said parameter selection means computes the difference and randomly selects parameters at which the difference satisfies a selection condition.

11. A system as set forth in claim 9, wherein the parameter selection reference information is a related degree between circumstances of use of elevator cars and each parameter and wherein said parameter selecting means weights selection probability of each parameter according to said related degree and thereby randomly selects said parameters.

12. A system as set forth in claim 9, wherein the parameter selection reference information is a related degree between contents of the performance estimation value and each parameter and wherein the parameter selecting means weights selection probability of each parameter according to the related degree and thereby randomly selects said parameters.

13. A system as set forth in claim 3, further comprising modifying means for modifying parameter selection reference information in accordance with proceeding circumstances of seeking.

14. A system as set forth in claim 2, further comprising probability modifying means for modifying selection probability of respective production methods in accordance with proceeding on-going circumstances of seeking.

15. A system as set forth in claim 14, wherein said probability modifying means computes a success index from a ratio of the number of sets which are added to said memorizing means to the number of estimated sets and modifies the selection probability based on the success index.

37. The system of claim 1, wherein the prediction data includes a prediction error rate and a prediction alteration rate for each set.

42. The system of claim 1, wherein each set includes at least about twenty-five parameter values.

16. A system for group managing a plurality of elevator cars according to a group management algorithm including:

group management apparatus for implementing a group management algorithm for controlling a plurality of elevators and for outputting a seeking condition signal, the seeking condition signal including at least one of;

traffic flow specification data, elevator car specification data, and seeking command data;

a plurality of parameters;

a seeking apparatus for seeking an optimum set from a plurality of sets, said seeking apparatus comprising;

memorizing means for storing a plurality of sets including parent sets, and group management performance data for each set, each set including a plurality of parameter values to be input into the group management algorithm, the group management performance data including information regarding a waiting time of an elevator user, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

numerical value exchanging means for producing two new sets partially inheriting a characteristic of the parent sets by exchanging a part of the parameter values of each parent set between the parent sets;

new value replacing means for producing one new set partially inheriting characteristics of one parent set selected from said memorizing means by replacing a part of the plurality of parameter values of the one parent set from said memorizing means with new numerical values generated in a random manner;

producing method selecting means for selecting a numerical value exchanging method and a new value replacing method in conjunction with a probability factor of each method;

estimating means for estimating a result of execution of the group management algorithm using the new set or sets in response to the seeking condition signal, the result of execution being group management performance data for each new set, the group management performance data including information regarding a waiting time of an elevator user, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

adding means for additionally storing in said memorizing means only new sets satisfying an adding condition, the adding condition being based on the group management performance data for each new set, said adding means storing in said memorizing means the group management performance data corresponding to each new set with each new set stored in said memorizing means;

deleting means for deleting from said memorizing means impaired sets satisfying a deletion condition, the deletion condition being based on the group management performance data of each impaired set, said deleting means deleting the group management performance data corresponding to each impaired set with each impaired set deleted from said memorizing means; and

extracting means for extracting an optimum set based on the group management performance data stored with the plurality of sets in said memorizing means.

17. A system as set forth in claim 16, further comprising modifying means for modifying the adding condition conditions.

18. A system as set forth in claim 17, wherein the adding condition is determined based on the group management performance data of respective sets stored in said memorizing means and is determined to be gradually stricter.

19. A system as set forth in claim 16, wherein said deleting means deletes sets whose performance estimation value is impaired.

20. A system as set forth in claim 19, wherein said deleting means deletes sets similar to another set based on the distance between sets.

21. A system as set forth in claim 16, further comprising initializing means for initializing seeking.

22. A system as set forth in claim 21, wherein:

said initializing means includes a first initialization mode and a second initialization mode;

in the first initialization mode, previously prepared plural sets are used for initialization; and

in the second initialization mode plural sets improved at the last seeking cycle are used for initialization, whereby in accordance with a seeking start condition, the first initialization mode and the second initialization mode are selected.

23. A system as set forth in claim 16, further comprising end judging means for judging the end of seeking in accordance with circumstances of seeking.

24. A system as set forth in claim 23, wherein said end judging means judges the end of seeking based on the number of estimated sets.

25. A system as set forth in claim 23, wherein said end judging means judges the end of seeking based on the number of added sets.

26. A system as set forth in claim 23, wherein said end judging means judges the end of seeking based on a success index as a ratio of the number of added sets to the number of estimated sets.

27. A system as set forth in claim 23, wherein said end judging means computes distance between sets with respect to the plural sets stored in said memorizing means and judges the end of seeking based on the distance between sets.

28. A system as set forth in claim 16, further comprising re-seeking judging means for judging re-seeking based on finding of a change of premises given at a time of seeking start.

29. A system as set forth in claim 16, wherein said seeking apparatus is connected with a target value setting apparatus for setting a target value in association with the process of seeking.

30. A system as set forth in claim 16, wherein said seeking apparatus is connected to a group management apparatus including the group management algorithm and controls operation of said plural elevator cars and is connected to a simulator including the same group management algorithm as that of said group management apparatus and wherein said estimating means sets the executed results of simulations as the group management performance data.

31. A system as set forth in claim 30, wherein said seeking apparatus and said simulator are provided remotely from said group management apparatus and wherein said seeking apparatus and said group management apparatus are linked by a communication line.

32. A system as set forth in claim 16, wherein said seeking apparatus is connected to a group management apparatus including the group management algorithm and controls operation of said plural elevator cars and wherein said estimating means sets the executed results at a time that said group management apparatus implements the simulation of the group management algorithm as the group management performance data.

33. A system as set forth in claim 32, wherein said seeking apparatus is provided remotely to said group management apparatus, and said seeking apparatus and said group management apparatus are linked by a communication line.

38. The system of claim 16, wherein the prediction data includes a prediction error rate and a prediction alteration rate for each set.

43. The system of claim 16 wherein each set includes at least about twenty-five parameter values.

34. A system for group managing a plurality of elevator cars according to a group management algorithm including:

a group management apparatus for implementing a group management algorithm for controlling a plurality of elevators and for outputting a seeking condition signal, the seeking condition signal including at least one of;

traffic flow specification data, elevator car specification data, and seeking command data;

a plurality of parameters; and

a seeking apparatus for seeking an optimum set from a plurality of sets, said seeking apparatus comprising;

memorizing means for storing a plurality of sets, including parent sets, and group management performance data for each set, each set including a plurality of parameter values to be input into the group management algorithm, the group management performance data including information regarding a waiting time of an elevator user, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

numerical value exchanging means for producing two new sets partially inheriting a characteristic of the parent sets by exchanging a part of the parameter values of each parent set between the parent sets;

new value replacing means for producing one new set partially inheriting characteristics of one parent set selected from said memorizing means by replacing a part of the plurality of parameter values of the one set with new numerical values generated in a random manner;

producing method selecting means for selecting a numerical value exchanging method and a new value replacing method in conjunction with a probability of each method;

estimating means for estimating a result of execution of the group management algorithm using the new set or sets in response to the seeking condition signal, the result of execution being group management performance data for each new set, the group management performance data including information regarding a waiting time of an elevator users, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

adding means for additionally storing in said memorizing means only new sets satisfying an adding condition, the adding condition being based on the group management performance data for each new set, the adding means storing the group management performance data corresponding to each new set with each new set stored in said memorizing means;

deleting means for deleting from said memorizing means impaired sets satisfying a deletion condition, the deletion condition being based on the group management performance data of each impaired set, said deleting means deleting the group management performance data corresponding to each impaired set along with each impaired set deleted from said memorizing means; and

extracting means for extracting an optimum set based on the group management performance data stored with the plurality of sets stored in said memorizing means.

39. The system of claim 34, wherein the prediction data includes a prediction error rate and a prediction alteration rate for each set.

44. The system of claim 34, wherein each set includes at least about twenty-five parameter values.

35. A system for group managing a plurality of elevator cars according to a group management algorithm including:

a group management apparatus for implementing a group management algorithm for controlling a plurality of elevators and for outputting a seeking condition signal, the seeking condition signal including at least one of;

traffic flow specification data, elevator car specification data, and seeking command data;

a plurality of parameters; and

a seeking apparatus for seeking an optimum set from a plurality of sets, said seeking apparatus comprising;

memorizing means for storing a plurality of sets and group management performance data for each set, each set including a plurality of parameter values to be input into the group management algorithm, the group management performance data including information regarding a waiting time of an elevator user, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

crossover producing means for producing two new sets partially inheriting characteristics of two parent sets selected from said memorizing means by exchanging a part of the plurality of parameter values between the two parent sets from said memorizing means;

estimating means for estimating a result of execution of the group management algorithm using the new set or sets in response to the seeking condition signal, the result of execution being group management performance data for each new set, the group management performance data including information regarding a waiting time of an elevator users, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from simulation of the group management algorithm using the respective sets;

selecting means for improving the plurality of sets stored in said memorizing means by adding the new sets to said memorizing means based on the group management performance data of each new set, said selecting means storing in said memorizing means the group management performance data corresponding to each new set with each new set stored in said memorizing means, and by deleting impaired sets from said memorizing means based on the group management performance data of each impaired set, said deleting means deleting the group management performance data corresponding to each of the impaired sets along with each impaired set deleted from said memorizing means; and

extracting means for extracting an optimum set based on the group management performance data of the plurality of sets stored in said memorizing means.

40. The system of claim 35, wherein the prediction data includes a prediction error rate and a prediction alteration rate for each set.

45. The system of claim 35, wherein each set includes at least about twenty-five parameter values.

36. A system for group managing a plurality of elevator cars according to a group management algorithm including a plurality of parameters, said system including:

a group management apparatus for implementing a group management algorithm for controlling a plurality of elevators and for outputting a seeking condition signal, the seeking condition signal including at least one of;

traffic flow specification data, elevator car specification data, and seeking command data; and

a seeking apparatus for seeking an optimum set from a plurality of sets, said seeking apparatus comprising;

memorizing means for storing a plurality of sets and group management performance data for each set, each set including a plurality of parameter values to be input into the group management algorithm, the group management performance data including information regarding a waiting time of an elevator user, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

mutation producing means for producing one new set partially inheriting a characteristic of one parent set selected from said memorizing means by replacing a part of the plurality parameter values of the one parent set with a new numerical value randomly generated;

estimating means for estimating a result of execution of the group management algorithm using the new set or sets in response to the seeking condition signal, the result of execution being group management performance data for each new set, the group management performance data including information regarding a waiting time of an elevator users, peak and average boarding time data, power consumption data, responding rate data, and prediction data resulting from execution of the group management algorithm using the respective sets;

selecting means for improving the plurality of sets stored in said memorizing means by adding the new set to said memorizing means based on the group management performance data of the new set, said selecting means storing in said memorizing means the group management performance data corresponding to the new set along with the new set in said memorizing means and by deleting an impaired set from said memorizing means based on the group management performance data of the impaired set, said selecting means deleting the group management performance data corresponding to the impaired set along with the impaired set; and

extracting means for extracting the optimum set based on the group management performance value among plural sets improved and stored in said memorizing means.

41. The system of claim 36, wherein the prediction data includes a prediction error rate and a prediction alteration rate for each set.

46. The system of claim 36, wherein each set includes at least about twenty-five parameter values.