SUBJECT OF THE INVENTION
The present invention relates to a method and an apparatus for allocating
calls given via the landing call devices of elevators comprised in an elevator group
so that each call is served by one elevator in the elevator group. In particular,
the invention relates to a method for stabilizing repeatedly defined allocation
decisions in an allocation system based on a genetic algorithm.
When a passenger wants a ride on an elevator, he calls an elevator
by pressing a landing call button on the floor. The elevator group control system
receives the call and tries to decide which one of the elevators in the elevator
group will be best suited to serve the call. This activity is call allocation. The
allocation function is a kind of minimization problem in which, as a solution to
the function, the aim is to find an elevator that minimizes the value of the function
on the basis of one or more selected cost factors.
When the number of calls and elevators serving them increases, the
minimization problem becomes significantly more complicated. This naturally increases
the amount of computation capacity required. The quantity to be minimized in the
allocation process may be passenger waiting time, passenger traveling time, number
of stops of the elevators, or a combination of several cost factors weighted in
Traditionally, when a suitable elevator is to be found for a call,
the reasoning is performed on a case-specific basis using complicated conditional
structures. The final objective of this reasoning is to minimize a given cost factor
describing the operation of the elevator group, typically the average passenger
waiting time. Since the possible combinations of states of the elevator group are
complex, the conditional structures are also complex and apt to have gaps, in other
words, there occur situations in which the control does not work in an optima way.
Likewise, it is difficult to take the entire elevator group into account as a whole.
A typical example of this is the traditional collective control, in which a landing
call is allocated to the elevator nearest to it and traveling in the direction of
However, this simple optimization principle leads to a grouping of
the elevators so that the elevators travel in a front in the same direction, and
therefore to a deterioration of the performance of the elevator group as a whole.
When the cost factors for all possible route alternatives are to be
determined, the required amount of computing work easily grows beyond the capacity
of the processors. If the number of calls to be served is C and the building has
L elevators, then the number of different route alternatives is N = LC.
As the number of route alternatives increases exponentially with increase of the
number of calls, systematic consideration of all route alternatives is impossible
even in small elevator groups. This has restricted the practical application of
Finnish patent application FI 951925 discloses a method for allocating
landing calls in an elevator group. This method is based on forming a plurality
of allocation options, each of which contains call data and elevator data for each
landing call, said data together defining the elevator which is to serve the landing
call. After this, the value of a cost function is computed for each allocation option
and one or more allocation options are altered in respect of one or more data items
comprised in it, whereupon the values of the cost functions of the new allocation
options thus obtained are computed. In this way, on the basis of the cost functions,
the best allocation option is selected and the currently active landing calls are
allocated accordingly to the elevators of the elevator group.
The solution according to FI 951925 substantially reduces the required
computation work as compared with calculating all possible route alternatives. In
a method based on a genetic algorithm like this, the elevator group is treated as
an entity, the cost function being optimized at the level of the entire elevator
group. The optimization can be performed without considering individual situations
and ways of coping with them. By modifying the cost function, a desired mode of
operation can be achieved. It is possible to optimize e.g. passenger waiting time,
call time, number of starts, traveling time, energy consumption, rope wear, operation
of an individual elevator if the use of a given elevator is expensive, uniform use
of the elevators and so on, or a desired combination of these.
If there are a large number of active landing calls, a single solution
or allocation option that is clearly better than other options will not necessarily
be found. To this situation, there are several solutions that are almost equally
good. This is a case of so-called multi-modality.
As the above-described genetic algorithm is a search method of a stochastic
nature, it does not guarantee that a search repeated over and over again will always
produce the same solution or allocation option, even if the same or almost the same
starting values are used. In the case of continuous allocation, this appears as
an instability of allocation decisions. The calls allocated to the elevators in
the elevator group change from one time of allocation to another. However, if it
is known that there are several approximately equally good allocation options for
the elevator group, then it does not make a difference which one of these allocation
options is used. By contrast, it is important that the allocation option should
not be altered each time the allocation option is selected again, but that a solution
once selected should be retained as long as the starting parameters of allocation
remain identical or sufficiently identical.
In practice, this means that, if the situation in the elevator group
remains unchanged, i.e. no more calls are received and no elevators are added or
removed from the group, then the elevator routes selected for a given set of calls
have to be retained until even the last call has been served. If this is not the
case, then an elevator in the elevator group may receive new control data every
half second, which is cumbersome for the elevator to implement and leads to instability
of the elevator group and the system.
The object of the invention is to disclose a new type of allocation
A specific object of the invention is to eliminate the above-mentioned
drawbacks of prior-art allocation methods or at least to provide a substantial improvement
A further alternative object of the invention is to disclose an allocation
method that is substantially more stable and reliable than prior-art methods.
A further alternative object of the invention is to make it possible
to stabilize the solution of an allocation problem and elevator group control so
that an unchanged or almost unchanged set of calls is served by an unchanged allocation
option as long as the allocation option in question produces a solution that is
one of the best solutions obtained by a stochastic selection process.
As for the features characteristic of the invention, reference is
made to the claims.
BRIEF DESCRIPTION OF THE INVENTION
The object of the invention is to achieve a new solution for allocating
landing calls to the elevators in an elevator group in such a way that the control
call received by each elevator changes as seldom as possible.
In the genetic method of the invention, to allocate calls to the elevators
in the elevator group, several allocation options, i.e. chromosomes are generated,
each of which contains for each active landing call a call data item and an elevator
data item, and these data items or genes together determine the elevator that is
to serve each landing call. For each chromosome generated, a fitness function value
is determined. Next, one or more of the chromosomes are altered in respect of at
least one gene, and fitness function values are determined for the chromosomes thus
obtained. The search, i.e. the generation of new chromosomes is continued until
an agreed termination condition is met, whereupon the best chromosome is selected
on the basis of the fitness function values and the calls are assigned according
to this solution to the elevators in the elevator group. Call allocation can be
repeated frequently, depending on different factors. In practice, the cycle of repetition
of allocation may be half a second or even shorter if necessary.
In the method of the invention, before a new search for a call allocation
decision or a new allocation cycle is started, the best chromosome selected before
is added to the set of chromosomes to direct the selection result to the best chromosome
selected before when the starting conditions of allocation are substantially unchanged.
In the method of the invention, a set of allocation options, i.e.
chromosomes form a generation, from which generally the best ones are selected for
reproduction to produce a new generation of chromosomes. The new generation is formed
from the selected chromosomes by means of a genetic algorithm via selection, cross-breeding
The procedure of the invention can be continued until the desired
target is reached, i.e. e.g. until a given fitness function value has been reached
or until a given number of new generations have been formed, or the procedure can
be interrupted upon the lapse of a given processing time. Another termination criterion
that may be applied is sufficient homogeneity of the population.
In the method of the invention, the best chromosome is added to the
first generation before a new generation is formed. The best chromosome may also
be added to the second generation or to one of the subsequent generations before
the formation of a new generation. In addition, the fitness function value of the
best chromosome of the preceding cycle may be multiplied by a constant K, which
preferably is smaller than unity, thus modifying the value of the fitness function.
After that, the chromosome provided with the modified fitness function is added
to the set of chromosomes.
If an "overgood" individual or chromosome is added to the population
during a new search cycle, i.e. at a new time of allocation, this increases the
stability of allocation decisions made via genetic allocation. Simply because an
"overgood" solution is the final result of the preceding allocation cycle, it causes
premature convergence of the population, in other words, it directs the population
towards the solution of the preceding cycle. According to relevant literature describing
genetic allocation, premature convergence is harmful expressly because an overgood
individual getting into the starting generation dominates the search for the best
alternative by communicating its genes to the population, with the result that the
population does not reach a solution to the set problem. However, the invention
expressly aims at reaching the solution of a previous cycle if the starting values
are the same or about the same.
The solution of the invention provides an excellent solution for the
stabilization of allocation decisions. If the situation in the elevator group remains
unchanged so that no additional calls are received and no elevators are removed
from or added to the group, then the elevator routes already found should be retained
long enough. On the other hand, if new calls appear in the system or the elevator
situation changes, then the form of the search space also changes, and a previously
selected good solution is no longer the best solution or one of the best solutions
in the search space. It is a poor solution among other poor solutions included in
the starting generation via the selection process.
The solution of the invention substantially reduces randomness in
the selection of the best allocation alternative for the elevators in an elevator
group. By applying the invention, it is possible to implement an integrated mechanism
for stabilizing elevator control decisions in an elevator control system that uses
genetic allocation. In addition, the invention makes it possible to introduce a
controlled hysteresis mechanism.
LIST OF DRAWINGS
In the following, the invention will be described in detail by the
aid of an embodiment example with reference to the attached drawings, wherein
- Fig. 1 illustrates the formation of an elevator chromosome,
- Fig. 2 represents a starting chromosome population according to the invention.
Fig. 1 is a diagram representing the floors of a building, which are
numbered 1, 2, 3..., 16. The elevator group comprises three elevators LIFT0, LIFT1
and LIFT2, which move in shafts 2, 4 and 6 and whose elevator cars are correspondingly
indicated by reference numbers 8, 10 and 12. The elevator cars are located at floors
3, 9 and 4 and their traveling direction is indicated by arrow symbols 14 shown
above the shaft, according to which elevator cars 8 and 12 are moving in the up
direction and elevator car 10 is moving in the down direction.
Beside the shafts there are columns 16 and 18 for active landing calls
for the down direction and the up direction. Landing calls are represented by arrow
symbols 20. An asterisk symbol indicates a car call issued from elevator car 10
to floor 1. Arrow symbols 24 indicate floors from which landing calls have been
issued and an elevator car has been allocated to the calls. Accordingly, the landing
call from floor 11 has been allocated to elevator LIFT0, the landing call from floor
7 has been allocated to elevator LIFT1 and the landing call from floor 14 has been
allocated to elevator LIFT2.
Columns 26 and 27 visualize the formation of an allocation option
when an elevator chromosome is used, one gene corresponding to each landing call.
Column 26 shows the active landing calls in order, the highest floor number being
placed topmost and the lowest floor number bottommost in the example in Fig. 1.
Column 27 contains the actual elevator chromosome, which, corresponding to the number
of landing calls, consists of five genes 30, which contain information regarding
the elevator serving the call. For each landing call there is one gene. Arrows 32
visualize the formation of a gene. According to elevator chromosome 27 and gene
102, elevator LIFT0 serves the call from floor 11. According to genes 100 and 101,
elevator LIFT1 serves the calls from floors 4 and 7, and similarly, according to
genes 103 and 104, elevator LIFT2 serves calls 13 and 14. During the formation of
the elevator chromosome, the active landing calls in the up and down directions
are encoded so that the position of the gene in the elevator chromosome carries
information about a landing call. After allocation has been performed, the information
of the elevator chromosome is decoded to corresponding landing calls.
Fig. 2 presents the principle of genetic allocation after the formation
of a chromosome. From the chromosomes, a population 34 comprising a selected number
Np of elevator chromosomes is generated. The chromosomes 1-np,
which are possible allocation alternatives for the existing calls, correspond to
the situation illustrated in Fig. 1, i.e. there are five down-calls from floors
4, 7,11, 13, 14 to be served. At first, each gene in the chromosomes comprised in
the population 34 is given a random elevator number or advance information is utilized
if available. Further, according to the invention, the genes of one chromosome 80
are assigned the values of the genes of the chromosome selected on the preceding
allocation cycle, in order from left to right LIFT0 LIFT0 LIFT2 LIFT2 LIFT1. At
this point, let it be noted that this is only an example of the selection chromosome
values and does not necessarily represent the best alternative in the case of Fig.
Further, the other chromosomes in the population are also given gene
values by selecting them at random or by using a previously known selection criterion.
Application FI 951925 contains a detailed description of the calculation and use
of the fitness function 28 in allocation and in the selection of the best chromosome.
Therefore, we shall not describe it in detail in the present application.
In the foregoing, the invention has been described by referring to
examples of its preferred embodiments. However, the invention is not intended to
be limited to these examples, but instead many variations are possible within the
sphere of protection of the claims presented below.