#! /usr/bin/env nix-shell #!nix-shell -i python3 -p python3 python3Packages.pyyaml -I nixpkgs=flake:nixpkgs # pip install pyyaml pyscipopt pyright import sys import yaml import re import argparse from collections import OrderedDict from pyscipopt import Model, quicksum from typing import Any, Tuple, TypeVar from dataclasses import dataclass, field conf = yaml.safe_load(open('config.yaml', 'r')) DEFAULT_CONFIG = { "max_load_person": 6 } config = DEFAULT_CONFIG | conf['config'] config['ignore'].append('') QUADRATIC = False @dataclass class TaskConfig: personen: list[str] workload: int req: list[int] hardcode: list[str] | None = None lookup: list[str] = field(default_factory=list) tasks: dict[str, TaskConfig] = OrderedDict({k: TaskConfig(**t) for k, t in conf['tasks'].items()}) X = TypeVar("X") def index(x: dict[X, Any]) -> dict[X, int]: return {v: k for k, v in enumerate(x)} daily_workloads = \ [sum(task.workload * task.req[d] for task in tasks.values()) for d in range(config['days'])] ALL_DAYS: set[int] = set(range(config['days'])) class Person(object): def __init__(self, conf={"dagen":ALL_DAYS}): self.can: set[str] = set() self.loves: set[str] = set() self.hates: set[str] = set() self.does: set[Tuple[int, str]] = set() # hardcoded self.has_prefs = False self.conf = conf self.conf['dagen'] = set(conf['dagen']) def vrolijkheid(self): res = config['days'] - len(self.does) for (_,t) in self.does: if t in self.loves: res += config['weights']['likes'] if t in self.hates: res -= config['weights']['hates'] return res def workload(self, tasks): return sum(tasks[t].workload for (_,t) in self.does) def cost(self, num_people): return round(sum((daily_workloads[d] for d in self.conf['dagen'])) / num_people) # probabilistic round: int(math.floor(x + random.random())) def read_people(conf_ppl) -> dict[str, Person]: people = OrderedDict() for x in conf_ppl: val = {"dagen": ALL_DAYS} if isinstance(x, dict): x,val = x.popitem() people[x.lower()] = Person(val) return people # deal with loves/hates def make_task_lut(tasks: dict[str, TaskConfig]): task_lut = {} for t, taskconf in tasks.items(): for lookup in taskconf.lookup: task_lut[lookup] = t task_re = re.compile(config['task_re']) def lookup_tasks(tasks): return (task_lut[x] for x in task_re.split(tasks) if x not in config['ignore']) return lookup_tasks def read_prefs(pref_file, tasks, people): lookup_tasks = make_task_lut(tasks) # read the wiki corvee table for [name, loves, hates] in ((q.strip().lower() for q in x.split('\t')) for x in pref_file): p = people[name] p.has_prefs = True p.loves |= set(lookup_tasks(loves)) p.hates |= set(lookup_tasks(hates)) for name, p in people.items(): if not p.has_prefs: print("warning: no preferences for", name, file=sys.stderr) # deal with capability and hardcode def set_capabilities(tasks: dict[str, TaskConfig], people: dict[str, Person]): for (task,conf) in tasks.items(): if conf.personen == 'iedereen': for p in people.values(): p.can.add(task) elif conf.personen == 'liefhebbers': for p in people.values(): if task in p.loves: p.can.add(task) else: for p in conf.personen: people[p.lower()].can.add(task) if conf.hardcode is not None: for day, pers in enumerate(conf.hardcode): people[pers.lower()].does.add((day, task)) def write_tasks(people, tasks, file=sys.stdout): for name, p in people.items(): days = [[] for i in range(config['days'])] for (d,t) in p.does: days[d].append((t, t in p.loves, t in p.hates)) def q(w): return ",".join([t + (" <3" if love else "") + (" :(" if hate else "") for (t,love,hate) in w]) days_fmt = " {} ||" * len(days) days_filled = days_fmt.format(*map(q, days)) print("| {} ||{} {} || {}".format(name, days_filled, p.vrolijkheid(), p.workload(tasks)), file=file) print("|-") def scipsol(people: dict[str, Person], tasks: dict[str, TaskConfig]): max_loads: dict[Tuple[str, int], int] = {} for i,p in people.items(): if 'max_load' in p.conf: # max_load override for Pol for d,load in enumerate(p.conf['max_load']): max_loads[(i,d)] = load # filter days that the person does not exist for d in ALL_DAYS - p.conf['dagen']: max_loads[(i,d)] = 0 m = Model() does = {} happiness = [] stdevs = [] errors = [] for pname, person in people.items(): workloads = [] p_error = m.addVar(vtype="I", name=f"{pname}_error", lb=0, ub=None) for d in ALL_DAYS: pdt = [] for task in tasks: var = m.addVar(vtype="B", name=f"{pname}_does_{task}@{d}") pdt.append(var) does[(pname, d, task)] = var # a person only does what (s)he is capable of if task not in person.can: m.addCons(var == 0) workloads.append(var * tasks[task].workload) for task in person.loves: happiness.append(does[(pname, d, task)] * config['weights']['likes']) for task in person.hates: happiness.append(does[(pname, d, task)] * (config['weights']['hates'] * -1)) # max_load_person: a person only has one task per day at most m.addCons(quicksum(pdt) <= max_loads.get((pname, d), 1)) m.addCons(p_error >= person.cost(len(people)) - quicksum(workloads)) m.addCons(p_error >= quicksum(workloads) - person.cost(len(people))) errors.append(p_error) stdevs.append((person.cost(len(people)) - quicksum(workloads)) ** 2) # min_load_person: person has at least 1 task m.addCons(quicksum([does[(pname, d, task)] for d in ALL_DAYS for task in tasks]) >= 1) # duplicate_jobs: a person does not perform the same job on all days for task in tasks: m.addCons(quicksum(does[(pname, d, task)] for d in ALL_DAYS) <= len(ALL_DAYS) - 1) # max_load_person_total m.addCons(quicksum([does[(pname, d, task)] * tasks[task].workload for d in ALL_DAYS for task in tasks]) <= config['max_load_person']) # hardcode constraint for d, task in person.does: m.addCons(does[(pname, d, task)] == 1) # all_allocated: each task in allocated for j in tasks: for d in ALL_DAYS: m.addCons(quicksum(does[(p, d, j)] for p in people) == tasks[j].req[d]) objective = m.addVar(name="objvar", vtype="C", lb=None, ub=None) m.setObjective(objective, "maximize") if QUADRATIC: m.addCons(objective <= quicksum(happiness) - quicksum(stdevs) / 2) else: if args.max_total_error is not None: m.addCons(quicksum(errors) <= args.max_total_error) m.addCons(objective <= quicksum(happiness) - quicksum(errors)) m.setObjective(objective, "maximize") m.solveConcurrent() for pname, person in people.items(): for d in ALL_DAYS: for task in tasks: if m.getVal(does[(pname, d, task)]): person.does.add((d, task)) write_tasks(people, tasks) print("Totale vrolijkheid:", sum(p.vrolijkheid() for p in people.values())) print("workload deviation:", m.getVal(quicksum(stdevs))) parser = argparse.ArgumentParser() parser.add_argument("-q", "--quadratic", action="store_true") parser.add_argument("--max_total_error", type=int, default=None) args = parser.parse_args() QUADRATIC = args.quadratic people = read_people(conf['people']) with open('prefs_table', 'r') as pref_file: read_prefs(pref_file, tasks, people) set_capabilities(tasks, people) scipsol(people, tasks)