Update (#26)

* Update * Update * Update * Update * Update * Update * Update * Update --------- Co-authored-by: LongxingTan <tanlongxing888@163.com>
yuetan1988 · Aug 9, 2023 · 7042313 · 7042313
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diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -21,7 +21,7 @@ repos:
     hooks:
     - id: black
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.3.1
+    rev: 1.2.3
     hooks:
       - id: nbqa-black
       - id: nbqa-isort

diff --git a/README.md b/README.md
@@ -30,13 +30,13 @@
 
 **[Documentation](https://python-lekin.readthedocs.io)** | **[Tutorials](https://python-lekin.readthedocs.io/en/latest/tutorials.html)** | **[Release Notes](https://python-lekin.readthedocs.io/en/latest/CHANGELOG.html)** | **[中文](https://github.com/LongxingTan/python-lekin/blob/master/README_zh_CN.md)**
 
-**python-lekin** is a rapid-to-implement and easy-to-use Flexible Job Shop Scheduler Library, named after and inspired by [Lekin](https://web-static.stern.nyu.edu/om/software/lekin/). As a core function in **APS (advanced planning and scheduler)**, it helps manufacturers optimize the allocation of raw materials and production capacity optimally to balance demand and capacity.
+**python-lekin** is a rapid-to-implement and easy-to-use Flexible Job Shop Scheduler Library, named after and inspired by [Lekin](https://web-static.stern.nyu.edu/om/software/lekin/). As a core function in **APS (advanced planning and scheduler)**, it helps manufacturers optimize the allocation of materials and production capacity optimally to balance demand and capacity.
 
 - accelerate by
 - Changeover Optimization
 - Ready for demo, research and maybe production
 
-# DRATFING- NOT FINISHED AND DON'T USE IT NOW!
+# **DRAFTING- NOT FINISHED AND DON'T USE IT NOW!**
 
 ## Feature
 

diff --git a/README_zh_CN.md b/README_zh_CN.md
@@ -29,13 +29,15 @@
 
 **python-lekin**是一个APS智能排产调度工具，名字来源于[Lekin](https://web-static.stern.nyu.edu/om/software/lekin/)。在考虑实际约束的前提下，动态调整计划排程，高效响应客户订单承诺。
 
-## 特征
 
 - 支持工艺路线约束
 - 支持产能约束
 - 支持物料齐套约束
 - 支持顺排、倒排等方法
+- 支持遗传算法排产
+- 支持强化学习排产
 
+# **DRAFTING- NOT FINISHED AND DON'T USE IT NOW!**
 
 ## 快速入门
 
@@ -57,18 +59,19 @@ scheduler.solve(jobs, machines)
 
 scheduler.draw()
 ```
-### 数据解释
-- Job
-- Task
-- Machine
-- Route
 
 ## 示例
 在实际APS系统开发中，
 
 - 按工艺路线拆分工序
 - 按BOM拆分物料
 
+### 数据准备
+- Job
+- Task
+- Machine
+- Route
+
 ## 引用
 
 ```

diff --git a/docs/source/application.rst b/docs/source/application.rst
@@ -1,6 +1,11 @@
 Application
 ===========
 
+基本概念
+----------------
+均衡生产：heijunka
+
+
 数据
 ----------------
 
@@ -41,6 +46,8 @@ BOM: Bill Of Materials
     ·更新当前任务后续节点的最早开工时间，若当前任务为产品的最后一个工序则无须更新
 8、判断所有任务是否均已完工，是则结束，否则返回步骤四。
 
+解决冲突的过程，即是一个顺排的过程。把所有分布在该资源上的任务根据顺序进行顺排
+
 
 可视化
 ------------

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -31,7 +31,7 @@ subject to:
 Finite Capacity Planning
 
 .. toctree::
-   :maxdepth: 5
+   :maxdepth: 2
    :caption: Contents:
 
    rules

diff --git a/docs/source/rules.rst b/docs/source/rules.rst
@@ -1,6 +1,7 @@
 Rules
 ============
 
+分为rule-based、event-based、resource-based两种思路。
 
 SPT最短加工时间
 --------------------

diff --git a/examples/basic_aps.py b/examples/basic_aps.py
diff --git a/examples/data/k1.json b/examples/data/k1.json
@@ -0,0 +1,129 @@
+{
+    "itineraries": [
+        {
+            "itineraryName": "Itinerary 1",
+            "tasksList": [
+                {
+                    "taskName": "Task 1",
+                    "taskMachine": {
+                        "machineName": "M1"
+                    },
+                    "taskDuration": 10.0
+                },
+                {
+                    "taskName": "Task 2",
+                    "taskMachine": {
+                        "machineName": "M2"
+                    },
+                    "taskDuration": 5.0
+                },
+                {
+                    "taskName": "Task 3",
+                    "taskMachine": {
+                        "machineName": "M3"
+                    },
+                    "taskDuration": 35.0
+                }
+            ]
+        },
+        {
+            "itineraryName": "Itinerary 2",
+            "tasksList": [
+                {
+                    "taskName": "Task 1",
+                    "taskMachine": {
+                        "machineName": "M2"
+                    },
+                    "taskDuration": 25.0
+                },
+                {
+                    "taskName": "Task 2",
+                    "taskMachine": {
+                        "machineName": "M1"
+                    },
+                    "taskDuration": 5.0
+                },
+                {
+                    "taskName": "Task 3",
+                    "taskMachine": {
+                        "machineName": "M3"
+                    },
+                    "taskDuration": 30.0
+                },
+                {
+                    "taskName": "Task 4",
+                    "taskMachine": {
+                        "machineName": "M4"
+                    },
+                    "taskDuration": 15.0
+                }
+            ]
+        },
+        {
+            "itineraryName": "Itinerary 3",
+            "tasksList": [
+                {
+                    "taskName": "Task 1",
+                    "taskMachine": {
+                        "machineName": "M2"
+                    },
+                    "taskDuration": 5.0
+                },
+                {
+                    "taskName": "Task 2",
+                    "taskMachine": {
+                        "machineName": "M4"
+                    },
+                    "taskDuration": 10.0
+                }
+            ]
+        },
+        {
+            "itineraryName": "Itinerary 4",
+            "tasksList": [
+                {
+                    "taskName": "Task 1",
+                    "taskMachine": {
+                        "machineName": "M2"
+                    },
+                    "taskDuration": 15.0
+                },
+                {
+                    "taskName": "Task 2",
+                    "taskMachine": {
+                        "machineName": "M3"
+                    },
+                    "taskDuration": 10.0
+                },
+                {
+                    "taskName": "Task 3",
+                    "taskMachine": {
+                        "machineName": "M4"
+                    },
+                    "taskDuration": 20.0
+                },
+                {
+                    "taskName": "Task 4",
+                    "taskMachine": {
+                        "machineName": "M1"
+                    },
+                    "taskDuration": 10.0
+                }
+            ]
+        }
+    ],
+    "machines": [
+        {
+            "machineName": "M1"
+        },
+        {
+            "machineName": "M2"
+        },
+        {
+            "machineName": "M3"
+        },
+        {
+            "machineName": "M4"
+        }
+    ]
+}
diff --git a/examples/rule_example1.py b/examples/rule_example1.py
@@ -0,0 +1,90 @@
+import json
+
+from lekin.dashboard.gantt import plot_gantt_chart
+from lekin.lekin_struct import (
+    Job,
+    JobCollector,
+    Operation,
+    OperationCollector,
+    Resource,
+    ResourceCollector,
+    Route,
+    RouteCollector,
+)
+from lekin.solver.construction_heuristics import LPSTScheduler, SPTScheduler
+
+
+def prepare_data(file_path="./data/k1.json"):
+    with open(file_path, "r", encoding="utf8") as file:  # read file from path
+        data = json.loads(file.read())
+
+    job_collector = JobCollector()
+    # operation_collector = OperationCollector()
+    route_collector = RouteCollector()
+    resource_collector = ResourceCollector()
+
+    if list(data.keys()) == ["itineraries", "machines"]:
+        resources = data["machines"]  # is first level structure is correct, then split
+        routes = data["itineraries"]
+
+        # parse the resource
+        for re in resources:
+            re_name = re["machineName"]
+            re_id = int(re_name.replace("M", ""))
+            resource = Resource(resource_id=re_id, resource_name=re_name)
+            resource_collector.add_resource_dict({re_id: resource})
+        print([i.resource_id for i in resource_collector.get_all_resources()])
+
+        # parse the job and route
+        for ro in routes:
+            # ro_name = ro["itineraryName"]
+            ro_id = int(ro["itineraryName"].replace("Itinerary ", ""))
+            route = Route(route_id=ro_id)
+            operations_sequence = []
+            for ta in ro["tasksList"]:
+                op_name = ta["taskName"]
+                op_id = ta["taskName"].replace("Task ", "")
+
+                op_pt = ta["taskDuration"]
+
+                op_tm = []
+                if isinstance(ta["taskMachine"], list):
+                    for re in ta["taskMachine"]:
+                        re_name = re["machineName"]
+                        re_id = int(re_name.replace("M", ""))
+                        op_tm.append(Resource(resource_id=re_id, resource_name=re_name))
+                else:
+                    re_name = ta["taskMachine"]["machineName"]
+                    re_id = int(re_name.replace("M", ""))
+                    op_tm.append(Resource(resource_id=re_id, resource_name=re_name))
+
+                operations_sequence.append(
+                    Operation(
+                        operation_id=op_id,
+                        operation_name=op_name,
+                        quantity=1,
+                        processing_time=op_pt,
+                        parent_job_id=ro_id,  # route defines job here
+                        available_resource=op_tm,
+                    )
+                )
+
+            route.operations_sequence = operations_sequence
+            route_collector.add_route(route)
+
+            job_collector.add_job(Job(job_id=ro_id, assigned_route_id=ro_id))
+
+        # print(resources)
+        print(routes)
+        pass
+    return job_collector, route_collector, resource_collector
+
+
+def run_scheduling(job_collector, route_list, resource_collector):
+    scheduler = SPTScheduler()
+    scheduler.solve(job_collector, resource_collector, route_list)
+    return
+
+
+if __name__ == "__main__":
+    prepare_data(file_path="./data/k1.json")
diff --git a/lekin/__init__.py b/lekin/__init__.py
@@ -5,7 +5,6 @@
 # from lekin.lekin_struct.operation import Operation
 # from lekin.lekin_struct.route import Route
 from lekin.scheduler import Scheduler
-from lekin.solver.construction_heuristics import Rules
 from lekin.solver.meta_heuristics import Heuristics
 
 __all__ = ["Job", "Machine", "Route", "Operation", "Scheduler", "get_data"]

diff --git a/lekin/lekin_struct/__init__.py b/lekin/lekin_struct/__init__.py
@@ -9,7 +9,7 @@
 """
 
 from lekin.lekin_struct.job import Job, JobCollector  # 成品需求
-from lekin.lekin_struct.operation import Operation  # 工序
+from lekin.lekin_struct.operation import Operation, OperationCollector  # 工序
 from lekin.lekin_struct.resource import Resource, ResourceCollector  # 机器
-from lekin.lekin_struct.route import Route
+from lekin.lekin_struct.route import Route, RouteCollector
 from lekin.lekin_struct.timeslot import TimeSlot