CN110175754B - Emergency resource allocation and transportation task planning method and system based on HTN planning - Google Patents

Emergency resource allocation and transportation task planning method and system based on HTN planning Download PDF

Info

Publication number
CN110175754B
CN110175754B CN201910366874.1A CN201910366874A CN110175754B CN 110175754 B CN110175754 B CN 110175754B CN 201910366874 A CN201910366874 A CN 201910366874A CN 110175754 B CN110175754 B CN 110175754B
Authority
CN
China
Prior art keywords
task
emergency
team
transport
transportation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910366874.1A
Other languages
Chinese (zh)
Other versions
CN110175754A (en
Inventor
祁超
王瑞
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Huazhong University of Science and Technology
Original Assignee
Huazhong University of Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Huazhong University of Science and Technology filed Critical Huazhong University of Science and Technology
Priority to CN201910366874.1A priority Critical patent/CN110175754B/en
Publication of CN110175754A publication Critical patent/CN110175754A/en
Application granted granted Critical
Publication of CN110175754B publication Critical patent/CN110175754B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Economics (AREA)
  • Operations Research (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Educational Administration (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses an HTN planning-based emergency resource allocation and transportation task planning method and system, which belong to the cross field of intelligent planning, public safety and emergency decision, and comprise the following steps: for an emergency resource allocation and transportation task to be planned, acquiring an initial state set and an initial task network set, and setting domain knowledge; decomposing an emergency resource allocation and transportation task to be planned into subtasks by combining an initial state set and an initial task network set by using a resource estimation method, an emergency resource allocation method and a transportation team selection method in the field knowledge; and then decomposing the subtasks by using an atomic task generation method in the domain knowledge to generate an atomic task, and instantiating and completing the atomic task by using an operational character in the domain knowledge to obtain an emergency resource allocation and transportation task planning scheme. The method can be well adapted to the problem of large-scale planning and complex planning, effectively describe the domain knowledge when expressing the problem of resource allocation and transportation, and well show the hierarchical characteristics of emergency response tasks.

Description

Emergency resource allocation and transportation task planning method and system based on HTN planning
Technical Field
The invention belongs to the crossing field of intelligent planning, public safety and emergency decision, and particularly relates to an emergency resource allocation and transportation task planning method and system based on HTN planning.
Background
The emergency resource allocation and transportation is taken as a key link of emergency response, is the key point of rescue work after disasters, and is related to life and property safety and social stability of the disaster victims, so that the emergency resource allocation and transportation has great practical significance for the research of the emergency resource allocation and transportation. Unlike traditional commercial logistics, the problem of emergency resource allocation and transportation has the following characteristics:
(1) tasks are diverse and hierarchical. After an earthquake occurs, the emergency resource allocation and transportation are divided into rescue personnel allocation and transportation, medical personnel allocation and transportation, living material allocation and transportation and the like, and the tasks are various rather than single; for the decomposition of a specific task, such as emergency resource guarantee of demand points, the type of emergency resource needs to be determined firstly, then the demand amount of the resource, then the resource allocation and the delivery of transport vehicles, and hierarchy exists among the decomposed tasks.
(2) The constraint relationship is complex. After an earthquake occurs, the types of emergency resources are numerous, the quantity in a short time is limited, the priority of tasks needs to be considered for allocating the emergency resources, and meanwhile, a complex constraint relation also exists between the tasks.
(3) The decision environment is highly dynamic. After an earthquake occurs, the evolution of the disaster changes along with the advance of time, so that the emergency situation changes all the time, and the debugging scheme needs to be changed continuously so as to adapt to the new emergency situation.
The above-described characteristics of the emergency resource allocation and transportation problem determine the difficulty in formulating an emergency resource allocation and transportation scheme. In practical problems, after an earthquake occurs, the formulation of an emergency resource allocation and transportation scheme mostly depends on the past experience of decision-making personnel, and a reasonable and satisfactory allocation and transportation scheme cannot be completely formulated; on the research level, most scholars at home and abroad aim at a local problem and carry out optimization solution based on a mathematical model. The mathematical model is established for solving, so that the method cannot be well adapted to the large-planning complex planning problem, such as the earthquake emergency resource allocation and transportation problem; secondly, when expressing the problem of resource allocation and transportation, the domain knowledge of the resource allocation and transportation cannot be effectively described, so that the problem that an emergency scheme maker solves the actual problem by utilizing the domain experience knowledge is limited, and meanwhile, the hierarchical characteristics of the emergency response task cannot be well expressed by a mathematical model.
In summary, establishing a mathematical model has certain limitations in solving the problem of emergency resource allocation and transportation.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides an emergency resource allocation and transportation Task planning method and system based on HTN (Hierarchical Task Network) planning, so that the technical problem that the prior art has certain limitation on solving the emergency resource allocation and transportation problem is solved.
To achieve the above object, according to an aspect of the present invention, there is provided an emergency resource allocation and transportation task planning method based on HTN planning, including the following steps:
for an emergency resource allocation and transportation task to be planned, acquiring an initial state set and an initial task network set, and setting domain knowledge;
decomposing an emergency resource allocation and transportation task to be planned into subtasks by combining an initial state set and an initial task network set by using a resource estimation method, an emergency resource allocation method and a transportation team selection method in the field knowledge;
and then decomposing the subtasks by using an atomic task generation method in the domain knowledge to generate an atomic task, and instantiating and completing the atomic task by using an operational character in the domain knowledge to obtain an emergency resource allocation and transportation task planning scheme.
Further, the initial state set is s0＝{SU0，TRANS0，SPEC0Dis }, wherein SU0Representing an initial set of states, TRANS, of emergency supplies reserves0Representing the initial set of states, SPEC, of the fleet0The initial state set of professional teams is shown, the professional teams comprise a rescue team, a medical team and an expert team, and the Dis shows an emergency resource allocation road network.
Further, the initial set of task networks is T0＝{t1，t2，t3，...}，ti＝(demand_location，intensity，population)，tiThe emergency resource network emergency resource guarantee and rescue method based on the cloud computing environment is characterized by comprising the following steps that a demand point is a resource guarantee and rescue task of a demand _ location, i is 1, 2 and 3, the demand _ location represents the position number of the demand point in an emergency resource network, intensity represents the seismic intensity of the demand point, and population represents the total population of the demand point.
Further, the domain knowledge D { O, M }, where O is an operator set, M is a method set, and the operator set O { |! move,! movep! transport }, operator! The movet instantiation is represented as a transfer action by the shipping team, operator! transport instantiation is represented as an emergency material transport action, operator! movep instantiation represents a professional team transfer action; the method set M ═ ResDemand, ResAllocation, TruckSelect, atomgeneration }, where ResDemand denotes a resource estimation method, ResAllocation denotes an emergency resource allocation method, TruckSelect denotes a transportation queue selection method, and atomgeneration denotes an atomic task generation method.
Further, the resource estimation method ResDemand ═ m1，m2，m3，m4，m5，m6The resource estimation method comprises the following steps:
judging the type of the needed upper layer emergency resources according to the earthquake intensity in the emergency resource allocation and transportation task to be planned, wherein the type of the upper layer emergency resources comprises living goods, rescue resources, medical resources and expert resources;
if the seismic intensity of the demand point is more than or equal to 6, entering the method m1Decomposing the emergency resource allocation and transportation task to be planned to generate a life material task, a rescue resource task, a medical resource task and an expert resource guarantee task;
if the seismic intensity of the demand point is less than 6, entering the method m2Decomposing the emergency resource allocation and transportation task to be planned to generate an expert resource guarantee task;
for the life material task, the type of the required upper layer emergency resource is life material, and the method m is entered3Calculating the required quantity of food, tents and drinking water in the lower-layer emergency resources;
for the rescue resource task, the type of the required upper layer emergency resource is the rescue resource, and the method m is entered4Calculating the demand of rescue teams in the lower-layer emergency resources;
for medical resource tasks, the type of the required upper-layer emergency resources is medical resources, and the method m is entered5Calculating the demand of medical teams in the lower layer of emergency resources;
for the expert resource task, the type of the required upper layer emergency resource is the expert resource, and the method m is entered6And calculating the demand of expert teams in the lower-layer emergency resources by using the seismic intensity.
Further, the emergency resource allocation method ResAllocation ═ { m ═ m7，m8，m9，m10The emergency resource allocation method comprises the following steps:
entering method m if the type of the lower layer emergency resource is professional team7Obtaining professional team allocation tasks; if the lower layer emergency resource type is the living material, entering the method m8Obtaining an emergency material distribution task;
if an emergency material distribution task is selected, entering a method m9Selecting an emergency material supply point closest to the demand point, if the emergency material reserve amount of the supply point meets the demand of the demand point, generating a transportation task transfer, and entering a transportation team selection method; if the emergency material reserve quantity of the supply point can not completely meet the demand, generating a transport task transfer, entering a transport team selection method, updating the emergency material reserve quantity of the supply point, updating the emergency material demand quantity of the current task, and entering the method m again9Selecting the next supply point closest to the demand point, and iteratively solving until the emergency resource demand of the demand point is met;
if professional team is selected to distribute tasks, the method m is entered10After the professional team closest to the demand point is obtained, if the professional team can meet the demand of the demand point, generating a professional team transfer task movep, and entering an atomic task generation method; if the professional team can not completely meet the requirements, generating a professional team transfer task movep, updating the state of the selected professional team, updating the professional team demand of the current task, and re-entering the method m10And selecting the next professional team closest to the demand point, and iteratively solving until the demand of the professional team of the demand point is met.
Further, the transportation team selection method TruckSelect ═ { m ═ m11，m12The method for selecting the transport team comprises the following steps:
reading the transport task transfer, entering method m11If the total transport volume is equal to 0, the transport task is finished, and the selection part of the transport team is finished;
if the total transport volume is larger than 0, reading the state of the transport team to obtain the position of the transport team, matching the position of the transport team with the position of the supply point to obtain a transport team set of the supply point, if the transport team set is not empty, selecting one transport team from the transport team set of the supply point to generate an emergency material transport task transport, and entering an atomic task generation method;
if the transportation team is gatheredFor null, enter method m12And selecting a transport team closest to the supply point, sequentially generating a transport team transfer task movet and an emergency material transport task transport, and entering the atomic task generation method.
Further, atomic task generation method atomGenerator ═ m13，m14，m15，m16，m17，m18The atomic task generation method comprises the following steps:
if the atomic task is a professional team transfer task movep, collecting { m) through the method17，m18Generation of an operator! movep, will operate! movep instantiation is professional team transfer action;
if the atomic task is an emergency material transportation task transport, the method is used for collecting { m }13，m14Generation of an operator! transport, transport! the transport is instantiated as an emergency material transportation action;
if the atomic task is a transportation team transfer task movet, the method is set to { m }15，m16Generation of an operator! movet, move operator! movet is instantiated as a transit team transfer action.
According to another aspect of the present invention, there is provided an emergency resource allocation and transportation task planning system based on HTN planning, comprising:
the system comprises a preprocessing module, a scheduling module and a scheduling module, wherein the preprocessing module is used for acquiring an initial state set and an initial task network set and setting domain knowledge for an emergency resource scheduling task to be planned;
the task decomposition module is used for decomposing the emergency resource dispatching and transporting task to be planned into subtasks by combining the initial state set and the initial task network set by utilizing a resource estimation method, an emergency resource allocation method and a transportation team selection method in the field knowledge;
and the task planning module is used for decomposing the subtasks by using an atomic task generation method in the domain knowledge to generate an atomic task, and instantiating and completing the atomic task by using an operational character in the domain knowledge to obtain an emergency resource allocation and transportation task planning scheme.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) the method for planning the emergency resource allocation and transportation task based on HTN planning can be well suitable for the problem of large-planning complex planning, such as solving the problem of planning the emergency resource allocation and transportation task under the earthquake background; secondly, when expressing the resource allocation and transportation problem, the domain knowledge can be effectively described, so that the emergency scheme maker can solve the actual problem by utilizing the domain experience knowledge, and simultaneously, the hierarchical characteristics of the emergency response task can be well expressed through task decomposition. In summary, the method of the present invention has strong applicability in solving the problem of emergency resource allocation and transportation.
(2) The method considers the characteristics and difficulties of the emergency resource allocation and transportation problem, such as task diversity, hierarchy, complex constraint relation, high dynamic property of decision environment and the like, and obtains a scientific and reasonable earthquake emergency resource allocation and transportation scheme based on an HTN planning method. The invention defines the knowledge in the field of emergency resource allocation and transportation facing HTN planning in detail, and further enriches the theoretical knowledge of the problem of emergency resource allocation and transportation; and secondly, decision support is provided for resource allocation and transportation in the emergency response process of the emergency, and certain practical significance is achieved.
Drawings
Fig. 1 is a flowchart of an emergency resource allocation and transportation task planning method based on HTN planning according to an embodiment of the present invention;
FIG. 2 is a flow chart of a resource estimation method provided by an embodiment of the invention;
fig. 3 is a flowchart of an emergency resource allocation method according to an embodiment of the present invention;
fig. 4 is a flowchart of a method for selecting a transportation team according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, an emergency resource allocation and transportation task planning method based on HTN planning includes the following steps:
for an emergency resource allocation and transportation task to be planned, acquiring an initial state set and an initial task network set, and setting domain knowledge;
decomposing an emergency resource allocation and transportation task to be planned into subtasks by combining an initial state set and an initial task network set by using a resource estimation method, an emergency resource allocation method and a transportation team selection method in the field knowledge;
and then decomposing the subtasks by using an atomic task generation method in the domain knowledge to generate an atomic task, and instantiating and completing the atomic task by using an operational character in the domain knowledge to obtain an emergency resource allocation and transportation task planning scheme.
Set of initial states as s0＝{SU0，TRANS0，SPEC0Dis }, wherein SU0Indicating an initial set of emergency material reserves, SU0＝{su1，su2，su3...}，Sui(i 1, 2, 3.) is the initial state, the emergency material reserve situation of a certain supply point in the road network. Sui＝{res1，res2，res3...}，resiAn initial state of some type of emergency supplies reserved for supply points; resiThe emergency material supply system comprises a road network, a road name, a road number, a road name, a road time axis, a road name, a. TRANS0Representing the initial set of states of the transporting team, TRANS0＝{trans1，trans2，trans3...}，transiShowing the initial state of a single transportation team; transi(CT), wherein transport team number is indicated by transport _ ID, and transport _ location indicates the position of the transport team in the road network at the current timeThe position number, truck _ capacity, indicates the capacity of the transportation team, and CT is the time axis of the transportation team.
SPEC0Represented is an initial set of states for a professional team, wherein the professional team comprises a rescue team, a medical team and an expert team, SPEC0＝{spec1，spec2，spec3...}，speciRepresenting an initial state of a single professional team; speciAnd { spec _ ID, spec _ location, spec _ type, spec _ hum, ST }, wherein the spec _ ID represents the number of the professional team, the spec _ location represents the number of the position of the professional team in the road network, and the spec _ type represents the type of the professional team. Dis denotes an emergency resource allocation and transportation road network, and Dis ═ seg1，seg2，seg3......}，segiInformation about a section of road in a road network is described. segiFrom _ node, to _ node, distance, access, from _ node, to _ node are two nodes of a section of road, and distance is the distance between the two nodes. The access represents the accessibility of the road, and when the access value is 0, the road interruption is represented; a value of 1 indicates that the road is clear.
The initial task network set is T0＝{t1，t2，t3，...}，ti＝(demand_location，intensity，population)，tiAnd the resource guarantee and rescue task with the demand point being demand _ location is shown. The demand _ location represents the position number of the demand point in the emergency resource road network, the intensity represents the disaster degree of the demand point, the earthquake intensity in the earthquake, and the population number of the demand point.
The domain knowledge D is specifically a binary D ═ O, M }, where O is an operator set and M is a method set. An operator of domain knowledge, which describes the preconditions and resulting effects of atomic task execution, can be expressed as a triple o ═ head (o), pre (o), update (o). Wherein, head (o) is the head of the operator, which contains the name of the operator and a set of parameters, pre (o) represents the precondition to be satisfied before the operator o is executed, and update (o) represents the effect after the operator o is executed, which includes the negative effect and the positive effect. Instantiation of an operator is an action that can be specifically performed; one approach in domain knowledge is to describe how to break up a compound task into a set of subtasks, where the set of subtasks consists of either compound tasks or atomic tasks. Method m may be expressed as the triplets m (head (m), pre (m), substtasks (m)). Head (m) represents the head of method m, contains the name of the method and a group of parameters, and is consistent with the name of the task and the parameters which can be decomposed by the method, pre (m) represents the precondition which is satisfied before the compound task is decomposed by the method m, and subtasks (m) represents the subtask set generated by the decomposition of the method m.
Wherein the operator set O {! move,! movep! transport }. An operator! The movet instantiation is represented as a transfer action by the shipping team, operator! transport instantiation is represented as an emergency material transport action, operator! movep represents a professional team transfer action;
the method set M ═ ResDemand, ResAllocation, TruckSelect, atomgeneration }. ResDemand represents a resource estimation method, and is m1，m2，m3，m4，m5，m6}; ResAllocation indicates an emergency resource allocation method, ResAllocation ═ m7，m8，m9，m10}; truckselect represents a method for selecting a transportation team, and is { m }11，m12}; atomGenerator denotes an atomic task generation method, atomGenerator ═ m13，m14，m15，m16，m17，m18}。
As shown in fig. 2, the resource estimation method includes the following steps:
and judging the type of the required upper layer emergency resource according to the seismic intensity in the emergency resource dispatching task (namely task demand) to be planned. The types of the upper layer emergency resources mainly comprise living goods, rescue resources, medical resources and expert resources.
Selecting an emergency resource guarantee task resource-demand, and carrying out specific demand estimation of lower-layer emergency resources:
if the seismic intensity of the demand point is greater than or equal to 6,entry method m1Decomposing the emergency resource allocation and transportation task to be planned to generate a life material task, a rescue resource task, a medical resource task and an expert resource guarantee task;
if the seismic intensity of the demand point is less than 6, entering the method m2Decomposing the emergency resource allocation and transportation task to be planned to generate an expert resource guarantee task;
for the life material task, the type of the required upper layer emergency resource is life material, and the method m is entered3The method comprises the following steps of calculating the required quantity of food, tents and drinking water in lower-layer emergency resources by only considering the requirement of earthquake gold rescue time of 72 hours, namely 3 days, and specifically comprises the following steps:
people＝population*damageratio
amout_food＝people*unit1*3
amout_water＝people*unit2*3
amout_tent＝people*unit3*3
wherein, peoples are the number of transfer and placement persons, population is the total population of disaster areas, damageatio is the serious damage rate of houses, and has a corresponding relation with earthquake intensity; the food demand is the unit1 food demand, the drinking water demand is the unit water demand, the unit2 drinking water demand is the unit water demand, the tent demand is the unit3 tent demand.
For the rescue resource task, the type of the required upper layer emergency resource is the rescue resource, and the method m is entered4Calculating the demand of rescue teams in the lower-layer emergency resources, and specifically comprising the following steps:
amout_rescuer＝persons/rescuer_num
persons＝population*collapseratio
wherein, persons is the number of people buried in the earthquake, population is the total population of demand points, collapseratio is the serious damage rate of the house and has a corresponding relation with the earthquake intensity, and reseter _ num is the number of people of a rescue team; and amout _ reserve is the demand of the rescue team.
For medical resource tasks, the type of the required upper-layer emergency resources is medical resources, and the method m is entered5Meter for measuringCalculating the demand ampout _ factor of the medical team in the lower-layer emergency resource specifically comprises the following steps:
amout_doctor＝persons/doctor_num
persons＝population*collapseratio
wherein, the persons is the number of the earthquake buried people, the population is the total population of the demand points, the collapseratio is the serious damage rate of the house and has a corresponding relation with the earthquake intensity, and the vector _ num is the number of people of one medical team.
For the expert resource task, the type of the required upper layer emergency resource is the expert resource, and the method m is entered6And calculating the demand of expert team in the lower layer emergency resource, wherein the demand has a corresponding relation with the seismic intensity.
As shown in fig. 3, the emergency resource allocation method includes the following steps:
judging the type of the lower layer emergency resource required by the task select, specifically:
entering method m if the type of the lower layer emergency resource is professional teams such as rescue teams, medical teams and expert teams7Obtaining a professional team allocation task spec-select;
entering method m if the type of the lower layer emergency resource is food, drinking water and living goods such as tent8Obtaining the supply-select of the emergency material distribution task;
if an emergency material distribution task is selected, entering a method m9. Selecting an emergency material supply point closest to a demand point by adopting a nearby available principle, generating a transportation task transfer if the emergency material reserve amount of the supply point meets the demand of the demand point, and entering a transportation team selection method;
if the emergency material reserve quantity of the supply point can not completely meet the demand, generating a transport task transfer, entering a transport team selection method, updating the emergency material reserve quantity of the supply point, updating the emergency material demand quantity of the current task, and entering the method m again9Selecting the next supply point closest to the demand point, and iteratively solving until the emergency resource demand of the demand point is met;
if professional team is selectedAllocating tasks and entering method m10After the professional team closest to the demand point is obtained, if the professional team can meet the demand of the demand point, generating a professional team transfer task movep, and entering an atomic task generation method;
if the professional team can not completely meet the requirements, generating a professional team transfer task movep, updating the state of the selected professional team, updating the professional team demand of the current task, and re-entering the method m10And selecting the next professional team closest to the demand point, and iteratively solving until the demand of the professional team of the demand point is met.
As shown in fig. 4, the method for selecting a transportation team includes the following steps:
reading the transfer of the current transportation task, and entering a method m11. If the total traffic is equal to 0, the transportation task is completed and the transportation team selection part is ended.
And if the total transport volume is larger than 0, reading the state of the current transport team to obtain the current position of the transport team, and matching the current position with the position of the supply point to obtain the transport team set at the position of the supply point. If the set is not empty, it indicates that the supply point currently has a transportation team. Selecting a transport team, generating an emergency material transport task transport, entering an atomic task generation method, updating the system state, and re-entering the method m11Iteratively solving until the transportation of the total transportation volume is finished;
if the collection is empty, the transportation team of the supply point is currently occupied, the transportation task is executed, and the method m is entered12The transport team closest to the supply point is selected. After a transport team with the nearest distance is selected, sequentially generating a transport team transfer task movet and an emergency material transport task transport, and entering an atomic task generation method;
after the transfer of the transportation team and the transportation of the emergency resources are finished, the system state is updated, and the method m is entered again12And iteratively solving to finish all traffic transportation. When the traffic volume is judged to be equal to 0, the transportation team selection section is ended.
The atomic task generation method comprises the following steps:
if the atomic task is a professional team transfer task movep, collecting { m) through the method17，m18Generation of an operator! movep, will operate! movep instantiation is professional team transfer action;
if the atomic task is an emergency material transportation task transport, the method is used for collecting { m }13，m14Generation of an operator! transport, transport! the transport is instantiated as an emergency material transportation action;
if the atomic task is a transportation team transfer task movet, the method is set to { m }15，m16Generation of an operator! movet, move operator! movet is instantiated as a transit team transfer action.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (8)

1. An HTN planning-based emergency resource allocation and transportation task planning method is characterized by comprising the following steps:
for an emergency resource allocation and transportation task to be planned, acquiring an initial state set and an initial task network set, and setting domain knowledge;
decomposing an emergency resource allocation and transportation task to be planned into subtasks by combining an initial state set and an initial task network set by using a resource estimation method, an emergency resource allocation method and a transportation team selection method in the field knowledge;
then decomposing the subtasks by using an atomic task generation method in the domain knowledge to generate an atomic task, and instantiating and completing the atomic task by using an operational character in the domain knowledge to obtain an emergency resource allocation and transportation task planning scheme;
the initial set of states is s0＝{SU0，TRANS0，SPEC0Dis }, wherein SU0Representing an initial set of states, TRANS, of emergency supplies reserves0Representing the initial set of states, SPEC, of the fleet0The method comprises the following steps that an initial state set of professional teams is shown, the professional teams comprise a rescue team, a medical team and an expert team, and an emergency resource allocation and transportation road network is shown by Dis;
SU0＝{su1，su2，su3，...，sui，...}，suiin the initial state, the emergency material reserve condition su of a certain supply point in the road networki＝{res1，res2，res3，...，resi，...}，resiAn initial state of some type of emergency supplies reserved for supply points; resiThe emergency material supply method comprises the steps of { supply _ location, resource _ name, supply _ num, RT }, wherein supply _ location represents the number of a supply point where an emergency material is located in a road network, resource _ name represents the type of the emergency material, supply _ num represents the reserve quantity of the emergency material, and RT represents an emergency material time axis;
TRANS0＝{trans1，trans2，trans3，...，transi，...}，transishowing the initial state of a single transportation team; transi(CT), wherein the truck _ ID represents a transport team number, the truck _ location represents a position number of a position of the current time of the transport team in a road network, the truck _ location represents the transport capacity of the transport team, and the CT is a time axis of the transport team;
SPEC0＝{spec1，spec2，spec3，...，speci，...}，specirepresenting an initial state of a single professional team; speciThe special team is selected from the group consisting of { spec _ ID, spec _ location, spec _ type, spec _ num and ST }, wherein the spec _ ID represents a special team number, the spec _ location represents a number of a position where the special team is located in the road network at present, and the spec _ type represents a type of the special team;
Dis＝{seg1，seg2，seg3，...，segi，...}，segidescribing relevant information of a section of road in a road network; segi＝{from_node，to_node，distance，access}，from_node，toThe _nodeis two nodes of a section of road, the distance is the distance between the two nodes, the access represents the accessibility of the road, and when the access value is 0, the road interruption is represented; a value of 1 indicates that the road is clear.
2. The method of claim 1, wherein the initial set of task networks is T, and wherein the initial set of task networks is T0＝{t1，t2，t3，...，ti，...}，ti＝{demand_location，intensity，population}，tiThe demand point is represented as a resource guarantee and rescue task of demand _ location, the demand _ location represents the position number of the demand point in an emergency resource road network, the intensity represents the seismic intensity of the demand point, and the population of the demand point represents the total population of the demand point.
3. An emergency resource commissioning mission planning method based on HTN planning as recited in claim 1 or 2 wherein said domain knowledge D { O, M }, wherein 0 is operator set, M is method set, operator set O { |! move,! movep! transport }, operator! The movet instantiation is represented as a transfer action by the shipping team, operator! transport instantiation is represented as an emergency material transport action, operator! movep instantiation represents a professional team transfer action; the method set M ═ ResDemand, ResAllocation, TruckSelect, atomgeneration }, where ResDemand denotes a resource estimation method, ResAllocation denotes an emergency resource allocation method, TruckSelect denotes a transportation queue selection method, and atomgeneration denotes an atomic task generation method.
4. An emergency resource allocation and transportation task planning method based on HTN planning as claimed in claim 1 or 2, wherein said resource estimation method ResDemand { m }1，m2，m3，m4，m5，m6The resource estimation method comprises the following steps:
judging the type of the needed upper layer emergency resources according to the earthquake intensity in the emergency resource allocation and transportation task to be planned, wherein the type of the upper layer emergency resources comprises living goods, rescue resources, medical resources and expert resources;
if the seismic intensity of the demand point is more than or equal to 6, entering the method m1Decomposing the emergency resource allocation and transportation task to be planned to generate a life material task, a rescue resource task, a medical resource task and an expert resource guarantee task;
if the seismic intensity of the demand point is less than 6, entering the method m2Decomposing the emergency resource allocation and transportation task to be planned to generate an expert resource guarantee task;
for the life material task, the type of the required upper layer emergency resource is life material, and the method m is entered3Calculating the required quantity of food, tents and drinking water in the lower-layer emergency resources;
for the rescue resource task, the type of the required upper layer emergency resource is the rescue resource, and the method m is entered4Calculating the demand of rescue teams in the lower-layer emergency resources;
for medical resource tasks, the type of the required upper-layer emergency resources is medical resources, and the method m is entered5Calculating the demand of medical teams in the lower layer of emergency resources;
for the expert resource task, the type of the required upper layer emergency resource is the expert resource, and the method m is entered6And calculating the demand of expert teams in the lower-layer emergency resources by using the seismic intensity.
5. The method of claim 4, wherein ResAllocation of Emergency resources is { m } m7，m8，m9，m10The emergency resource allocation method comprises the following steps:
entering method m if the type of the lower layer emergency resource is professional team7Obtaining professional team allocation tasks; if the lower layer emergency resource type is the living material, entering the method m8Obtaining an emergency material distribution task;
if an emergency material distribution task is selected, the entering partyMethod m9Selecting an emergency material supply point closest to the demand point, if the emergency material reserve amount of the supply point meets the demand of the demand point, generating a transportation task transfer, and entering a transportation team selection method; if the emergency material reserve quantity of the supply point can not completely meet the demand, generating a transport task transfer, entering a transport team selection method, updating the emergency material reserve quantity of the supply point, updating the emergency material demand quantity of the current task, and entering the method m again9Selecting the next supply point closest to the demand point, and iteratively solving until the emergency resource demand of the demand point is met;
if professional team is selected to distribute tasks, the method m is entered10After the professional team closest to the demand point is obtained, if the professional team can meet the demand of the demand point, generating a professional team transfer task movep, and entering an atomic task generation method; if the professional team can not completely meet the requirements, generating a professional team transfer task movep, updating the state of the selected professional team, updating the professional team demand of the current task, and re-entering the method m10And selecting the next professional team closest to the demand point, and iteratively solving until the demand of the professional team of the demand point is met.
6. The method for planning emergency resource allocation and transportation task based on HTN planning of claim 5, wherein said transportation team selection method TruckSelect { m ═ m }11，m12The method for selecting the transport team comprises the following steps:
reading the transport task transfer, entering method m11If the total transport volume is equal to 0, the transport task is finished, and the selection part of the transport team is finished;
if the total transport volume is larger than 0, reading the state of the transport team to obtain the position of the transport team, matching the position of the transport team with the position of the supply point to obtain a transport team set of the supply point, if the transport team set is not empty, selecting one transport team from the transport team set of the supply point to generate an emergency material transport task transport, and entering an atomic task generation method;
entering method m if the transport team set is empty12And selecting a transport team closest to the supply point, sequentially generating a transport team transfer task movet and an emergency material transport task transport, and entering the atomic task generation method.
7. The method of claim 6, wherein the atomic task generation method AtomGenerator { m } is used for planning the emergency resource allocation and transportation task based on HTN planning13，m14，m15，m16，m17，m18The atomic task generation method comprises the following steps:
if the atomic task is a professional team transfer task movep, collecting { m) through the method17，m18Generation of an operator! movep, will operate! movep instantiation is professional team transfer action;
if the atomic task is an emergency material transportation task transport, the method is used for collecting { m }13，m14Generation of an operator! transport, transport! the transport is instantiated as an emergency material transportation action;
if the atomic task is a transportation team transfer task movet, the method is set to { m }15，m16Generation of an operator! movet, move operator! movet is instantiated as a transit team transfer action.
8. An emergency resource allocation and transportation task planning system based on HTN planning is characterized by comprising:
the system comprises a preprocessing module, a scheduling module and a scheduling module, wherein the preprocessing module is used for acquiring an initial state set and an initial task network set and setting domain knowledge for an emergency resource scheduling task to be planned;
the task decomposition module is used for decomposing the emergency resource dispatching and transporting task to be planned into subtasks by combining the initial state set and the initial task network set by utilizing a resource estimation method, an emergency resource allocation method and a transportation team selection method in the field knowledge;
the task planning module is used for decomposing the subtasks by using an atomic task generation method in the domain knowledge to generate an atomic task, and instantiating and completing the atomic task by using an operational character in the domain knowledge to obtain an emergency resource allocation and transportation task planning scheme;
the initial set of states is s0＝{SU0，TRANS0，SPEC0Dis }, wherein SU0Representing an initial set of states, TRANS, of emergency supplies reserves0Representing the initial set of states, SPEC, of the fleet0The method comprises the following steps that an initial state set of professional teams is shown, the professional teams comprise a rescue team, a medical team and an expert team, and an emergency resource allocation and transportation road network is shown by Dis;
SU0＝{su1，su2，su3，...，sui，...}，suiin the initial state, the emergency material reserve condition su of a certain supply point in the road networki＝{res1，res2，res3，...，resi，...}，resiAn initial state of some type of emergency supplies reserved for supply points; resiThe emergency material supply method comprises the steps of { supply _ location, resource _ name, supply _ num, RT }, wherein supply _ location represents the number of a supply point where an emergency material is located in a road network, resource _ name represents the type of the emergency material, supply _ num represents the reserve quantity of the emergency material, and RT represents an emergency material time axis;
TRANS0＝{trans1，trans2，trans3，...，transi，...}，transishowing the initial state of a single transportation team; transi(CT), wherein the truck _ ID represents a transport team number, the truck _ location represents a position number of a position of the current time of the transport team in a road network, the truck _ location represents the transport capacity of the transport team, and the CT is a time axis of the transport team;
SPEC0＝{spec1，spec2，spec3，...，speci，...}，specirepresenting an initial state of a single professional team; speci{ spec _ ID, spec _ location, spec _ type, spec _ num, ST }, where spec _ ID represents a professional team number, spec _ location represents a number of a current position of the professional team in a road network, and spec _ type represents a type of the professional team;
Dis＝{seg1，seg2，seg3，...，segi，...}，segidescribing relevant information of a section of road in a road network; segiFrom _ node, to _ node, distance, and access, where from _ node and to _ node are two nodes of a road segment, distance is the distance between the two nodes, access represents the reachability of the road, and when the access value is 0, it represents the road interruption; a value of 1 indicates that the road is clear.
CN201910366874.1A 2019-04-30 2019-04-30 Emergency resource allocation and transportation task planning method and system based on HTN planning Active CN110175754B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910366874.1A CN110175754B (en) 2019-04-30 2019-04-30 Emergency resource allocation and transportation task planning method and system based on HTN planning

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910366874.1A CN110175754B (en) 2019-04-30 2019-04-30 Emergency resource allocation and transportation task planning method and system based on HTN planning

Publications (2)

Publication Number Publication Date
CN110175754A CN110175754A (en) 2019-08-27
CN110175754B true CN110175754B (en) 2021-08-31

Family

ID=67690557

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910366874.1A Active CN110175754B (en) 2019-04-30 2019-04-30 Emergency resource allocation and transportation task planning method and system based on HTN planning

Country Status (1)

Country Link
CN (1) CN110175754B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113705970A (en) * 2021-07-28 2021-11-26 北京联合大学 HTN planning method for emergency logistics resource task matching

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7676539B2 (en) * 2005-06-09 2010-03-09 International Business Machines Corporation Methods, apparatus and computer programs for automated problem solving in a distributed, collaborative environment
CN102044022A (en) * 2010-12-24 2011-05-04 中国科学院合肥物质科学研究院 Emergency rescue decision making system aiming at natural disasters and method thereof
GB201313712D0 (en) * 2013-07-31 2013-09-11 Ibm Optimizing emergency resources in case of disaster
CN107220749A (en) * 2017-05-11 2017-09-29 长威信息科技发展股份有限公司 A kind of method and system of emergency resources fast dispatch
CN107346470A (en) * 2017-06-19 2017-11-14 长安大学 A kind of Intelligent planning method towards traffic-information service
CN108335024B (en) * 2018-01-23 2020-08-04 华中科技大学 Shipboard aircraft continuous action task planning method and task planning description method
CN109063949B (en) * 2018-06-12 2022-05-17 中国科学技术大学 Chemical industry park centralized area emergency material allocation method based on ultra-network

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Handling multi-objective in an HTN planner for emergency decision-making;Minglei Li等;《IEEE Conference Anthology》;20140410;第1-5页 *

Also Published As

Publication number Publication date
CN110175754A (en) 2019-08-27

Similar Documents

Publication Publication Date Title
Barbarosoğlu et al. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations
WO2021248607A1 (en) Deep reinforcement learning-based taxi dispatching method and system
Allahviranloo et al. Selective vehicle routing problems under uncertainty without recourse
Skobelev Multi-agent systems for real-time adaptive resource management
Zhu IOT and big data based cooperative logistical delivery scheduling method and cloud robot system
Mejia‐Argueta et al. Multicriteria optimization approach to deploy humanitarian logistic operations integrally during floods
CN101515309A (en) City emergency evacuation simulation system based on multi intelligent agent
CN105678411A (en) Passenger train operation scheme diagram drawing method
Liu et al. Distributing UAVs as wireless repeaters in disaster relief via group role assignment
Li et al. Design of multimodal hub-and-spoke transportation network for emergency relief under COVID-19 pandemic: A meta-heuristic approach
Yang et al. Onboard coordination and scheduling of multiple autonomous satellites in an uncertain environment
CN110175754B (en) Emergency resource allocation and transportation task planning method and system based on HTN planning
CN114706672B (en) Satellite autonomous mission planning system and method based on event-driven dynamic assembly
Parygin Implementation of exoactive management model for urbanized area: real-time monitoring and proactive planning
Li et al. An artificial emergency-logistics-planning system for severe disasters
Nourjou et al. Introduction to spatially distributed intelligent assistant agents for coordination of human-agent teams' actions
Postránecký et al. Assessment method to measure smartness of cities
Shen et al. A dynamic task assignment model for aviation emergency rescue based on multi-agent reinforcement learning
Radzki et al. Periodic planning of UAVs' fleet mission with the uncertainty of travel parameters
CN116883704A (en) Giant constellation collaborative earth observation task planning optimization method, equipment and medium
Yang et al. The two-stage integrated allocation model for local emergency supplies
Maruyama et al. Development of virtual and real-field construction management systems in innovative, intelligent field factory
Hirai et al. An algorithm for train rescheduling using rescheduling pattern description language R
Churiakova et al. Digital Master Plan as a Tool for Generating Territory Development Requirements
CN110782180A (en) Blackboard model-based multi-satellite task online distribution method and system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant