Flexible Job Shop Problem with Machine Changeover Times
Problem
In the Flexible Job Shop Scheduling Problem with Machine-Dependent Changeover Times, a set of jobs has to be processed on the machines in the shop. Each job consists of an ordered sequence of tasks (called operations), and each operation must be performed by one of the machines compatible with that operation. Each operation has a given processing time that depends on the chosen machine, and each machine can only process one operation at a time. An operation cannot begin until the previous operation in the job is completed. Furthermore, there is a changeover time between two consecutive operations in the same job that are not processed by the same machine. This changeover time depends on the machines used for the two operations. The objective is to minimize the makespan, which is the time when all jobs have ended.
Principles learned
- Add interval decision variables to model the tasks
- Add list decision variables to model the assignment of tasks on the machines and their order
- Define lambda functions to link the interval and list variables together
Data
The instances we provide come from the Brandimarte [1] dataset. Their format is as follows:
- First line: number of jobs, number of machines, average number of machines per operation (not needed)
- From the second line, for each job:
- Number of operations in that job
- For each operation:
- Number of machines compatible with this operation
- For each compatible machine: machine index and processing time on this machine
- For each pair of machines:
- Changeover time between these two machines
Program
The Hexaly model for the Flexible Job Shop Scheduling Problem with Machine-Dependent Changeover Times uses interval decision variables to model the time ranges of the operations, and list decision variables to represent the order of the tasks scheduled on each machine.
Using the ‘partition‘ operator, we ensure that each task is assigned to exactly one machine. For each operation, we filter out incompatible machines thanks to the ‘contains’ operator. Using the ‘find‘ operator, we can then retrieve the index of the machine that was chosen to process each task. This allows us to deduce the processing time of each operation, which depends on the chosen machine, and to constrain the length of each interval accordingly.
The precedence constraints are easily written. For each job, each operation of this job must start after the end of the previous operation plus the changeover time, which depends on the machines chosen for these operations. The disjunctive resource constraints can be formulated as follows: for all i, the task processed in position i+1 must start after the end of the task processed in position i. To model this constraint, we define a lambda function expressing the relationship between two consecutive activities. This function is then used within a variadic ‘and’ operator over all tasks processed processed by each machine. Note that the number of terms inside these ‘and’ expressions varies during the search, along with the size of the lists (the number of tasks assigned to each machine).
The objective consists in minimizing the makespan, which is the time when all the tasks have ended.
- Execution
-
hexaly flexiblejobshop_changeover.hxm inFileName=instances/Mk01.fjsc [outFileName=] [hxTimeLimit=]
use io;
/* Read instance data */
function input() {
local usage = "Usage: hexaly flexiblejobshop_changeover.hxm inFileName=instanceFile"
+ " [outFileName=outputFile] [hxTimeLimit=timeLimit]";
if (inFileName == nil) throw usage;
// Constant for incompatible machines
INFINITE = 1000000;
inFile = io.openRead(inFileName);
// Number of jobs
nbJobs = inFile.readInt();
// Number of machines
nbMachines = inFile.readInt();
inFile.readln(); // skip last number
// Number of tasks
nbTasks = 0;
processingTime = {};
// Processing time for each task, for each machine
taskProcessingTime = {};
// For each job, for each operation, the corresponding task id
jobOperationTask = {};
for [j in 0...nbJobs] {
// Number of operations for each job
nbOperations[j] = inFile.readInt();
for [o in 0...nbOperations[j]] {
local nbMachinesOperation = inFile.readInt();
for [i in 0...nbMachinesOperation] {
local machine = inFile.readInt() - 1;
local time = inFile.readInt();
processingTime[j][o][machine] = time;
taskProcessingTime[nbTasks][machine] = time;
}
jobOperationTask[j][o] = nbTasks;
nbTasks += 1;
}
}
// Changeover time between two machines
for [m1 in 0...nbMachines] {
for [m2 in 0...nbMachines] {
machineChangeoverTime[m1][m2] = inFile.readInt();
}
}
inFile.close();
// Trivial upper bound for the start times of the tasks
maxStart = 0;
for [j in 0...nbJobs][o in 0...nbOperations[j]] {
local maxProcessingTime = 0;
for [m in 0...nbMachines] {
if (processingTime[j][o][m] == nil) {
local task = jobOperationTask[j][o];
taskProcessingTime[task][m] = INFINITE;
} else if (processingTime[j][o][m] >= maxProcessingTime) {
maxProcessingTime = processingTime[j][o][m];
}
}
maxStart += maxProcessingTime;
}
}
/* Declare the optimization model */
function model() {
// Sequence of tasks on each machine
jobsOrder[m in 0...nbMachines] <- list(nbTasks);
// Each task is scheduled on a machine
constraint partition[m in 0...nbMachines](jobsOrder[m]);
// Only compatible machines can be selected for a task
for [i in 0...nbTasks][m in 0...nbMachines : taskProcessingTime[i][m] == INFINITE]
constraint !contains(jobsOrder[m], i);
// For each task, the selected machine
taskMachine[i in 0...nbTasks] <- find(jobsOrder, i);
// Interval decisions: time range of each task
tasks[i in 0...nbTasks] <- interval(0, maxStart);
// The task duration depends on the selected machine
duration[i in 0...nbTasks] <- taskProcessingTime[i][taskMachine[i]];
for [i in 0...nbTasks]
constraint length(tasks[i]) == duration[i];
// Precedence constraints between the operations of a job with machine-dependent changeover times
for [j in 0...nbJobs][o in 0...nbOperations[j]-1] {
local i1 = jobOperationTask[j][o];
local i2 = jobOperationTask[j][o + 1];
constraint start(tasks[i2]) >= end(tasks[i1])
+ machineChangeoverTime[taskMachine[i1]][taskMachine[i2]];
}
// Disjunctive resource constraints between the tasks on a machine
for [m in 0...nbMachines] {
local sequence <- jobsOrder[m];
constraint and(0...count(sequence)-1,
i => tasks[sequence[i]] < tasks[sequence[i + 1]]);
}
// Minimize the makespan: end of the last task
makespan <- max[i in 0...nbTasks](end(tasks[i]));
minimize makespan;
}
/* Parameterize the solver */
function param() {
if (hxTimeLimit == nil) hxTimeLimit = 60;
}
/* Write the solution in a file with the following format:
* - for each operation of each job, the selected machine, the start and end dates */
function output() {
if (outFileName != nil) {
outFile = io.openWrite(outFileName);
println("Solution written in file ", outFileName);
for [j in 0...nbJobs][o in 0...nbOperations[j]] {
local taskIndex = jobOperationTask[j][o];
outFile.println(j + 1, "\t", o + 1, "\t", taskMachine[taskIndex].value + 1,
"\t", tasks[taskIndex].value.start, "\t", tasks[taskIndex].value.end);
}
}
}
- Execution (Windows)
-
set PYTHONPATH=%HX_HOME%\bin\pythonpython flexiblejobshop_changeover.py instances\Mk01.fjsc
- Execution (Linux)
-
export PYTHONPATH=/opt/hexaly_13_0/bin/pythonpython flexiblejobshop_changeover.py instances/Mk01.fjsc
import hexaly.optimizer
import sys
# Constant for incompatible machines
INFINITE = 1000000
def read_instance(filename):
with open(filename) as f:
lines = f.readlines()
first_line = lines[0].split()
# Number of jobs
nb_jobs = int(first_line[0])
# Number of machines
nb_machines = int(first_line[1])
# Number of operations for each job
nb_operations = [int(lines[j + 1].split()[0]) for j in range(nb_jobs)]
# Number of tasks
nb_tasks = sum(nb_operations[j] for j in range(nb_jobs))
# Processing time for each task, for each machine
task_processing_time = [[INFINITE for m in range(nb_machines)] for i in range(nb_tasks)]
# For each job, for each operation, the corresponding task id
job_operation_task = [[0 for o in range(nb_operations[j])] for j in range(nb_jobs)]
id = 0
for j in range(nb_jobs):
line = lines[j + 1].split()
tmp = 0
for o in range(nb_operations[j]):
nb_machines_operation = int(line[tmp + o + 1])
for i in range(nb_machines_operation):
machine = int(line[tmp + o + 2 * i + 2]) - 1
time = int(line[tmp + o + 2 * i + 3])
task_processing_time[id][machine] = time
job_operation_task[j][o] = id
id = id + 1
tmp = tmp + 2 * nb_machines_operation
# Changeover time between two machines
machine_changeover_time = [[0 for m2 in range(nb_machines)] for m1 in range(nb_machines)]
for m1 in range(nb_machines):
line = lines[nb_jobs + 1 + m1].split()
for m2 in range(nb_machines):
machine_changeover_time[m1][m2] = int(line[m2])
# Trivial upper bound for the start times of the tasks
max_start = sum(
max(task_processing_time[i][m] for m in range(nb_machines) if task_processing_time[i][m] != INFINITE)
for i in range(nb_tasks))
return nb_jobs, nb_machines, nb_tasks, task_processing_time, job_operation_task, nb_operations, max_start, machine_changeover_time
def main(instance_file, output_file, time_limit):
nb_jobs, nb_machines, nb_tasks, task_processing_time_data, job_operation_task, \
nb_operations, max_start, machine_changeover_time_data = read_instance(instance_file)
with hexaly.optimizer.HexalyOptimizer() as optimizer:
#
# Declare the optimization model
#
model = optimizer.model
# Sequence of tasks on each machine
jobs_order = [model.list(nb_tasks) for _ in range(nb_machines)]
machines = model.array(jobs_order)
# Each task is scheduled on a machine
model.constraint(model.partition(machines))
# Only compatible machines can be selected for a task
for i in range(nb_tasks):
for m in range(nb_machines):
if task_processing_time_data[i][m] == INFINITE:
model.constraint(model.not_(model.contains(jobs_order[m], i)))
# For each task, the selected machine
task_machine = [model.find(machines, i) for i in range(nb_tasks)]
task_processing_time = model.array(task_processing_time_data)
# Interval decisions: time range of each task
tasks = [model.interval(0, max_start) for _ in range(nb_tasks)]
# The task duration depends on the selected machine
duration = [model.at(task_processing_time, i, task_machine[i]) for i in range(nb_tasks)]
for i in range(nb_tasks):
model.constraint(model.length(tasks[i]) == duration[i])
task_array = model.array(tasks)
machine_changeover_time = model.array(machine_changeover_time_data)
# Precedence constraints between the operations of a job with machine-dependent changeover times
for j in range(nb_jobs):
for o in range(nb_operations[j] - 1):
i1 = job_operation_task[j][o]
i2 = job_operation_task[j][o + 1]
model.constraint(model.start(tasks[i2]) >= model.end(tasks[i1])
+ machine_changeover_time[task_machine[i1]][task_machine[i2]])
# Disjunctive resource constraints between the tasks on a machine
for m in range(nb_machines):
sequence = jobs_order[m]
sequence_lambda = model.lambda_function(
lambda i: task_array[sequence[i]] < task_array[sequence[i + 1]])
model.constraint(model.and_(model.range(0, model.count(sequence) - 1), sequence_lambda))
# Minimize the makespan: end of the last task
makespan = model.max([model.end(tasks[i]) for i in range(nb_tasks)])
model.minimize(makespan)
model.close()
# Parameterize the optimizer
optimizer.param.time_limit = time_limit
optimizer.solve()
# Write the solution in a file with the following format:
# - for each operation of each job, the selected machine, the start and end dates
if output_file != None:
with open(output_file, "w") as f:
print("Solution written in file", output_file)
for j in range(nb_jobs):
for o in range(0, nb_operations[j]):
taskIndex = job_operation_task[j][o]
f.write(str(j + 1) + "\t" + str(o + 1)
+ "\t" + str(task_machine[taskIndex].value + 1)
+ "\t" + str(tasks[taskIndex].value.start())
+ "\t" + str(tasks[taskIndex].value.end()) + "\n")
if __name__ == '__main__':
if len(sys.argv) < 2:
print("Usage: python flexiblejobshop_changeover.py instance_file [output_file] [time_limit]")
sys.exit(1)
instance_file = sys.argv[1]
output_file = sys.argv[2] if len(sys.argv) >= 3 else None
time_limit = int(sys.argv[3]) if len(sys.argv) >= 4 else 60
main(instance_file, output_file, time_limit)
- Compilation / Execution (Windows)
-
cl /EHsc flexiblejobshop_changeover.cpp -I%HX_HOME%\include /link %HX_HOME%\bin\hexaly130.libflexiblejobshop_changeover instances\Mk01.fjsc
- Compilation / Execution (Linux)
-
g++ flexiblejobshop_changeover.cpp -I/opt/hexaly_13_0/include -lhexaly130 -lpthread -o flexiblejobshop_changeover./flexiblejobshop_changeover instances/Mk01.fjsc
#include "optimizer/hexalyoptimizer.h"
#include <algorithm>
#include <fstream>
#include <iostream>
#include <limits>
#include <numeric>
#include <vector>
using namespace hexaly;
class FlexibleJobshop {
private:
// Number of jobs
int nbJobs;
// Number of machines
int nbMachines;
// Number of tasks
int nbTasks;
// Processing time for each task, for each machine
std::vector<std::vector<int>> taskProcessingTimeData;
// Changeover time between two machines
std::vector<std::vector<int>> machineChangeoverTimeData;
// For each job, for each operation, the corresponding task id
std::vector<std::vector<int>> jobOperationTask;
// Number of operations for each job
std::vector<int> nbOperations;
// Trivial upper bound for the start times of the tasks
int maxStart;
// Constant for incompatible machines
const int INFINITE = 1000000;
// Hexaly Optimizer
HexalyOptimizer optimizer;
// Decision variables: time range of each task
std::vector<HxExpression> tasks;
// Decision variables: sequence of tasks on each machine
std::vector<HxExpression> jobsOrder;
// For each task, the selected machine
std::vector<HxExpression> taskMachine;
// Objective = minimize the makespan: end of the last task
HxExpression makespan;
public:
FlexibleJobshop() : optimizer() {}
void readInstance(const std::string& fileName) {
std::ifstream infile;
infile.exceptions(std::ifstream::failbit | std::ifstream::badbit);
infile.open(fileName.c_str());
infile >> nbJobs;
infile >> nbMachines;
infile.ignore(std::numeric_limits<std::streamsize>::max(), '\n'); // skip last number
nbTasks = 0;
std::vector<std::vector<std::vector<int>>> processingTime = std::vector<std::vector<std::vector<int>>>(nbJobs);
jobOperationTask.resize(nbJobs);
nbOperations.resize(nbJobs);
for (unsigned int j = 0; j < nbJobs; ++j) {
infile >> nbOperations[j];
jobOperationTask[j].resize(nbOperations[j]);
processingTime[j].resize(nbOperations[j]);
for (unsigned int o = 0; o < nbOperations[j]; ++o) {
int nbMachinesOperation;
infile >> nbMachinesOperation;
taskProcessingTimeData.push_back(std::vector<int>(nbMachines, INFINITE));
processingTime[j][o].resize(nbMachines, INFINITE);
for (int m = 0; m < nbMachinesOperation; ++m) {
int machine;
int time;
infile >> machine;
infile >> time;
processingTime[j][o][machine - 1] = time;
taskProcessingTimeData[nbTasks][machine - 1] = time;
}
jobOperationTask[j][o] = nbTasks;
nbTasks += 1;
}
}
machineChangeoverTimeData = std::vector<std::vector<int>>(nbMachines, std::vector<int>(nbMachines));
for (unsigned int m1 = 0; m1 < nbMachines; ++m1){
for (unsigned int m2 = 0; m2 < nbMachines; ++m2){
infile >> machineChangeoverTimeData[m1][m2];
}
}
infile.close();
// Trivial upper bound for the start times of the tasks
maxStart = 0;
for (unsigned int j = 0; j < nbJobs; ++j) {
for (unsigned int o = 0; o < nbOperations[j]; ++o) {
int maxProcessingTime = 0;
for (unsigned int m = 0; m < nbMachines; ++m) {
if (processingTime[j][o][m] != INFINITE && processingTime[j][o][m] > maxProcessingTime)
maxProcessingTime = processingTime[j][o][m];
}
maxStart += maxProcessingTime;
}
}
}
void solve(int timeLimit) {
// Declare the optimization model
HxModel model = optimizer.getModel();
// Sequence of tasks on each machine
jobsOrder.resize(nbMachines);
HxExpression machines = model.array();
for (unsigned int m = 0; m < nbMachines; ++m) {
jobsOrder[m] = model.listVar(nbTasks);
machines.addOperand(jobsOrder[m]);
}
// Each task is scheduled on a machine
model.constraint(model.partition(machines));
// Only compatible machines can be selected for a task
for (int i = 0; i < nbTasks; ++i) {
for (unsigned int m = 0; m < nbMachines; ++m) {
if (taskProcessingTimeData[i][m] == INFINITE) {
model.constraint(!model.contains(jobsOrder[m], i));
}
}
}
taskMachine.resize(nbTasks);
HxExpression taskProcessingTime = model.array();
for (int i = 0; i < nbTasks; ++i) {
// For each task, the selected machine
taskMachine[i] = model.find(machines, i);
taskProcessingTime.addOperand(
model.array(taskProcessingTimeData[i].begin(), taskProcessingTimeData[i].end()));
}
tasks.resize(nbTasks);
std::vector<HxExpression> duration(nbTasks);
for (int i = 0; i < nbTasks; ++i) {
// Interval decisions: time range of each task
tasks[i] = model.intervalVar(0, maxStart);
// The task duration depends on the selected machine
duration[i] = model.at(taskProcessingTime, i, taskMachine[i]);
model.constraint(model.length(tasks[i]) == duration[i]);
}
HxExpression taskArray = model.array(tasks.begin(), tasks.end());
HxExpression machineChangeoverTime = model.array();
for (int m1 = 0; m1 < nbMachines; ++m1) {
machineChangeoverTime.addOperand(
model.array(machineChangeoverTimeData[m1].begin(), machineChangeoverTimeData[m1].end()));
}
// Precedence constraints between the operations of a job with machine-dependent changeover times
for (unsigned int j = 0; j < nbJobs; ++j) {
for (unsigned int o = 0; o < nbOperations[j] - 1; ++o) {
int i1 = jobOperationTask[j][o];
int i2 = jobOperationTask[j][o + 1];
model.constraint(model.start(tasks[i2]) >= model.end(tasks[i1])
+ machineChangeoverTime[taskMachine[i1]][taskMachine[i2]]);
}
}
// Disjunctive resource constraints between the tasks on a machine
for (int m = 0; m < nbMachines; ++m) {
HxExpression sequence = jobsOrder[m];
HxExpression sequenceLambda = model.createLambdaFunction(
[&](HxExpression i) { return taskArray[sequence[i]] < taskArray[sequence[i + 1]]; });
model.constraint(model.and_(model.range(0, model.count(sequence) - 1), sequenceLambda));
}
// Minimize the makespan: end of the last task
makespan = model.max();
for (int i = 0; i < nbTasks; ++i) {
makespan.addOperand(model.end(tasks[i]));
}
model.minimize(makespan);
model.close();
// Parameterize the optimizer
optimizer.getParam().setTimeLimit(timeLimit);
optimizer.solve();
}
/* Write the solution in a file with the following format:
* - for each operation of each job, the selected machine, the start and end dates */
void writeSolution(const std::string& fileName) {
std::ofstream outfile(fileName.c_str());
if (!outfile.is_open()) {
std::cerr << "File " << fileName << " cannot be opened." << std::endl;
exit(1);
}
std::cout << "Solution written in file " << fileName << std::endl;
for (unsigned int j = 0; j < nbJobs; ++j) {
for (unsigned int o = 0; o < nbOperations[j]; ++o) {
int taskIndex = jobOperationTask[j][o];
outfile << j + 1 << "\t" << o + 1 << "\t" << taskMachine[taskIndex].getValue() + 1 << "\t"
<< tasks[taskIndex].getIntervalValue().getStart() << "\t"
<< tasks[taskIndex].getIntervalValue().getEnd() << std::endl;
}
}
outfile.close();
}
};
int main(int argc, char** argv) {
if (argc < 2) {
std::cout << "Usage: flexiblejobshop_changeover instanceFile [outputFile] [timeLimit]" << std::endl;
exit(1);
}
const char* instanceFile = argv[1];
const char* outputFile = argc > 2 ? argv[2] : NULL;
const char* strTimeLimit = argc > 3 ? argv[3] : "60";
FlexibleJobshop model;
try {
model.readInstance(instanceFile);
const int timeLimit = atoi(strTimeLimit);
model.solve(timeLimit);
if (outputFile != NULL)
model.writeSolution(outputFile);
return 0;
} catch (const std::exception& e) {
std::cerr << "An error occurred: " << e.what() << std::endl;
return 1;
}
}
- Compilation / Execution (Windows)
-
copy %HX_HOME%\bin\Hexaly.NET.dll .csc FlexibleJobshopChangeover.cs /reference:Hexaly.NET.dllFlexibleJobshopChangeover instances\Mk01.fjsc
using System;
using System.IO;
using System.Linq;
using Hexaly.Optimizer;
public class FlexibleJobshopChangeover : IDisposable
{
// Number of jobs
private int nbJobs;
// Number of machines
private int nbMachines;
// Number of tasks
private int nbTasks;
// Processing time for each task, for each machine
private long[][] taskProcessingTimeData;
// Changeover time between two machines
private int[][] machineChangeoverTimeData;
// For each job, for each operation, the corresponding task id
private int[][] jobOperationTask;
// Number of operations for each job;
private int[] nbOperations;
// Trivial upper bound for the start times of the tasks
private long maxStart;
// Constant for incompatible machines
private const long INFINITE = 1000000;
// Hexaly Optimizer
private HexalyOptimizer optimizer;
// Decision variables: time range of each task
private HxExpression[] tasks;
// Decision variables: sequence of tasks on each machine
private HxExpression[] jobsOrder;
// For each task, the selected machine
private HxExpression[] taskMachine;
// Objective = minimize the makespan: end of the last task
private HxExpression makespan;
public FlexibleJobshopChangeover()
{
optimizer = new HexalyOptimizer();
}
public void ReadInstance(string fileName)
{
using (StreamReader input = new StreamReader(fileName))
{
char[] separators = new char[] { '\t', ' ' };
string[] splitted = input
.ReadLine()
.Split(separators, StringSplitOptions.RemoveEmptyEntries);
nbJobs = int.Parse(splitted[0]);
nbMachines = int.Parse(splitted[1]);
nbTasks = 0;
long[][][] processingTime = new long[nbJobs][][];
jobOperationTask = new int[nbJobs][];
nbOperations = new int[nbJobs];
for (int j = 0; j < nbJobs; ++j)
{
splitted = input
.ReadLine()
.Split(separators, StringSplitOptions.RemoveEmptyEntries);
nbOperations[j] = int.Parse(splitted[0]);
jobOperationTask[j] = new int[nbOperations[j]];
processingTime[j] = new long[nbOperations[j]][];
int k = 1;
for (int o = 0; o < nbOperations[j]; ++o)
{
int nbMachinesOperation = int.Parse(splitted[k]);
k++;
processingTime[j][o] = Enumerable.Repeat((long)INFINITE, nbMachines).ToArray();
for (int m = 0; m < nbMachinesOperation; ++m)
{
int machine = int.Parse(splitted[k]) - 1;
long time = long.Parse(splitted[k + 1]);
processingTime[j][o][machine] = time;
k += 2;
}
jobOperationTask[j][o] = nbTasks;
nbTasks++;
}
}
machineChangeoverTimeData = new int[nbMachines][];
for (int m1 = 0; m1 < nbMachines; ++m1)
{
machineChangeoverTimeData[m1] = new int[nbTasks];
splitted = input.
ReadLine()
.Split(separators, StringSplitOptions.RemoveEmptyEntries);
machineChangeoverTimeData[m1] = new int[nbMachines];
for (int m2 = 0; m2 < nbMachines; ++m2)
{
machineChangeoverTimeData[m1][m2] = int.Parse(splitted[m2]);
}
}
// Trivial upper bound for the start times of the tasks
maxStart = 0;
taskProcessingTimeData = new long[nbTasks][];
for (int j = 0; j < nbJobs; ++j)
{
long maxProcessingTime = 0;
for (int o = 0; o < nbOperations[j]; ++o)
{
int task = jobOperationTask[j][o];
taskProcessingTimeData[task] = new long[nbMachines];
for (int m = 0; m < nbMachines; ++m)
{
taskProcessingTimeData[task][m] = processingTime[j][o][m];
if (
processingTime[j][o][m] != INFINITE
&& processingTime[j][o][m] > maxProcessingTime
)
{
maxProcessingTime = processingTime[j][o][m];
}
}
maxStart += maxProcessingTime;
}
}
}
}
public void Dispose()
{
optimizer.Dispose();
}
public void Solve(int timeLimit)
{
// Declare the optimization model
HxModel model = optimizer.GetModel();
// Sequence of tasks on each machine
jobsOrder = new HxExpression[nbMachines];
HxExpression machines = model.Array();
for (int m = 0; m < nbMachines; ++m)
{
jobsOrder[m] = model.List(nbTasks);
machines.AddOperand(jobsOrder[m]);
}
// Each task is scheduled on a machine
model.Constraint(model.Partition(machines));
// Only compatible machines can be selected for a task
for (int i = 0; i < nbTasks; ++i)
{
for (int m = 0; m < nbMachines; ++m)
{
if (taskProcessingTimeData[i][m] == INFINITE)
model.Constraint(!model.Contains(jobsOrder[m], i));
}
}
// For each task, the selected machine
taskMachine = new HxExpression[nbTasks];
for (int i = 0; i < nbTasks; ++i)
{
taskMachine[i] = model.Find(machines, i);
}
tasks = new HxExpression[nbTasks];
HxExpression[] duration = new HxExpression[nbTasks];
HxExpression taskProcessingTime = model.Array(taskProcessingTimeData);
for (int i = 0; i < nbTasks; ++i)
{
// Interval decisions: time range of each task
tasks[i] = model.Interval(0, maxStart);
// The task duration depends on the selected machine
HxExpression iExpr = model.CreateConstant(i);
duration[i] = model.At(taskProcessingTime, iExpr, taskMachine[i]);
model.Constraint(model.Length(tasks[i]) == duration[i]);
}
HxExpression taskArray = model.Array(tasks);
HxExpression machineChangeoverTime = model.Array(machineChangeoverTimeData);
// Precedence constraints between the operations of a job with machine-dependent changeover times
for (int j = 0; j < nbJobs; ++j)
{
for (int o = 0; o < nbOperations[j] - 1; ++o)
{
int i1 = jobOperationTask[j][o];
int i2 = jobOperationTask[j][o + 1];
model.Constraint(model.Start(tasks[i2]) >= model.End(tasks[i1])
+ machineChangeoverTime[taskMachine[i1]][taskMachine[i2]]);
}
}
// Disjunctive resource constraints between the tasks on a machine
for (int m = 0; m < nbMachines; ++m)
{
HxExpression sequence = jobsOrder[m];
HxExpression sequenceLambda = model.LambdaFunction(
i => taskArray[sequence[i]] < taskArray[sequence[i + 1]]
);
model.Constraint(model.And(model.Range(0, model.Count(sequence) - 1), sequenceLambda));
}
// Minimize the makespan: end of the last task
makespan = model.Max();
for (int i = 0; i < nbTasks; ++i)
{
makespan.AddOperand(model.End(tasks[i]));
}
model.Minimize(makespan);
model.Close();
// Parameterize the optimizer
optimizer.GetParam().SetTimeLimit(timeLimit);
optimizer.Solve();
}
/* Write the solution in a file with the following format:
* - for each operation of each job, the selected machine, the start and end dates */
public void WriteSolution(string fileName)
{
using (StreamWriter output = new StreamWriter(fileName))
{
Console.WriteLine("Solution written in file " + fileName);
for (int j = 1; j <= nbJobs; ++j)
{
for (int o = 1; o <= nbOperations[j - 1]; ++o)
{
int taskIndex = jobOperationTask[j - 1][o - 1];
output.WriteLine(
j
+ "\t"
+ o
+ "\t"
+ taskMachine[taskIndex].GetValue()
+ "\t"
+ tasks[taskIndex].GetIntervalValue().Start()
+ "\t"
+ tasks[taskIndex].GetIntervalValue().End()
);
}
}
}
}
public static void Main(string[] args)
{
if (args.Length < 1)
{
Console.WriteLine("Usage: FlexibleJobshopChangeover instanceFile [outputFile] [timeLimit]");
System.Environment.Exit(1);
}
string instanceFile = args[0];
string outputFile = args.Length > 1 ? args[1] : null;
string strTimeLimit = args.Length > 2 ? args[2] : "60";
using (FlexibleJobshopChangeover model = new FlexibleJobshopChangeover())
{
model.ReadInstance(instanceFile);
model.Solve(int.Parse(strTimeLimit));
if (outputFile != null)
model.WriteSolution(outputFile);
}
}
}
- Compilation / Execution (Windows)
-
javac FlexibleJobshopChangeover.java -cp %HX_HOME%\bin\hexaly.jarjava -cp %HX_HOME%\bin\hexaly.jar;. FlexibleJobshopChangeover instances\Mk01.fjsc
- Compilation / Execution (Linux)
-
javac FlexibleJobshopChangeover.java -cp /opt/hexaly_13_0/bin/hexaly.jarjava -cp /opt/hexaly_13_0/bin/hexaly.jar:. FlexibleJobshopChangeover instances/Mk01.fjsc
import java.util.*;
import java.io.*;
import com.hexaly.optimizer.*;
public class FlexibleJobshopChangeover {
// Number of jobs
private int nbJobs;
// Number of machines
private int nbMachines;
// Number of tasks
private int nbTasks;
// Processing time for each task, for each machine
private long[][] taskProcessingTimeData;
// Changeover time between two machines
private int[][] machineChangeoverTimeData;
// For each job, for each operation, the corresponding task id
private int[][] jobOperationTask;
// Number of operations for each job;
private int[] nbOperations;
// Trivial upper bound for the start times of the tasks
private long maxStart;
// Constant for incompatible machines
private final int INFINITE = 1000000;
// Hexaly Optimizer
final HexalyOptimizer optimizer;
// Decision variables: time range of each task
private HxExpression[] tasks;
// Decision variables: sequence of tasks on each machine
private HxExpression[] jobsOrder;
// For each task, the selected machine
private HxExpression[] taskMachine;
// Objective = minimize the makespan: end of the last task
private HxExpression makespan;
public FlexibleJobshopChangeover(HexalyOptimizer optimizer) throws IOException {
this.optimizer = optimizer;
}
public void readInstance(String fileName) throws IOException {
try (Scanner input = new Scanner(new File(fileName))) {
nbJobs = input.nextInt();
nbMachines = input.nextInt();
input.next(); // skip last number
nbTasks = 0;
long[][][] processingTime = new long[nbJobs][][];
jobOperationTask = new int[nbJobs][];
nbOperations = new int[nbJobs];
for (int j = 0; j < nbJobs; ++j) {
nbOperations[j] = input.nextInt();
jobOperationTask[j] = new int[nbOperations[j]];
processingTime[j] = new long[nbOperations[j]][nbMachines];
for (int o = 0; o < nbOperations[j]; ++o) {
int nbMachinesOperation = input.nextInt();
Arrays.fill(processingTime[j][o], INFINITE);
for (int m = 0; m < nbMachinesOperation; ++m) {
int machine = input.nextInt() - 1;
long time = input.nextLong();
processingTime[j][o][machine] = time;
}
jobOperationTask[j][o] = nbTasks;
nbTasks++;
}
}
machineChangeoverTimeData = new int[nbMachines][nbMachines];
for (int m1 = 0; m1 < nbMachines; ++m1) {
for (int m2 = 0; m2 < nbMachines; ++m2) {
machineChangeoverTimeData[m1][m2] = input.nextInt();
}
}
// Trivial upper bound for the start times of the tasks
maxStart = 0;
taskProcessingTimeData = new long[nbTasks][];
for (int j = 0; j < nbJobs; ++j) {
long maxProcessingTime = 0;
for (int o = 0; o < nbOperations[j]; ++o) {
int task = jobOperationTask[j][o];
taskProcessingTimeData[task] = new long[nbMachines];
for (int m = 0; m < nbMachines; ++m) {
taskProcessingTimeData[task][m] = processingTime[j][o][m];
if (processingTime[j][o][m] != INFINITE && processingTime[j][o][m] > maxProcessingTime) {
maxProcessingTime = processingTime[j][o][m];
}
}
maxStart += maxProcessingTime;
}
}
}
}
public void solve(int timeLimit) {
// Declare the optimization model
HxModel model = optimizer.getModel();
// Sequence of tasks on each machine
jobsOrder = new HxExpression[nbMachines];
HxExpression machines = model.array();
for (int m = 0; m < nbMachines; ++m) {
jobsOrder[m] = model.listVar(nbTasks);
machines.addOperand(jobsOrder[m]);
}
// Each task is scheduled on a machine
model.constraint(model.partition(machines));
// Only compatible machines can be selected for a task
for (int i = 0; i < nbTasks; ++i) {
for (int m = 0; m < nbMachines; ++m) {
if (taskProcessingTimeData[i][m] == INFINITE) {
model.constraint(model.not(model.contains(jobsOrder[m], i)));
}
}
}
// For each task, the selected machine
taskMachine = new HxExpression[nbTasks];
for (int i = 0; i < nbTasks; ++i) {
taskMachine[i] = model.find(machines, i);
}
HxExpression taskProcessingTime = model.array(taskProcessingTimeData);
tasks = new HxExpression[nbTasks];
HxExpression[] duration = new HxExpression[nbTasks];
for (int i = 0; i < nbTasks; ++i) {
// Interval decisions: time range of each task
tasks[i] = model.intervalVar(0, maxStart);
// The task duration depends on the selected machine
HxExpression iExpr = model.createConstant(i);
duration[i] = model.at(taskProcessingTime, iExpr, taskMachine[i]);
model.constraint(model.eq(model.length(tasks[i]), duration[i]));
}
HxExpression taskArray = model.array(tasks);
HxExpression machineChangeoverTime = model.array(machineChangeoverTimeData);
// Precedence constraints between the operations of a job with machine-dependent changeover times
for (int j = 0; j < nbJobs; ++j) {
for (int o = 0; o < nbOperations[j] - 1; ++o) {
int i1 = jobOperationTask[j][o];
int i2 = jobOperationTask[j][o + 1];
model.constraint(model.geq(model.start(tasks[i2]), model.sum(model.end(tasks[i1]),
model.at(machineChangeoverTime, taskMachine[i1], taskMachine[i2]))));
}
}
// Disjunctive resource constraints between the tasks on a machine
for (int m = 0; m < nbMachines; ++m) {
HxExpression sequence = jobsOrder[m];
HxExpression sequenceLambda = model.lambdaFunction(i -> model
.lt(model.at(taskArray, model.at(sequence, i)),
model.at(taskArray, model.at(sequence, model.sum(i, 1)))));
model.constraint(model.and(model.range(0, model.sub(model.count(sequence), 1)), sequenceLambda));
}
// Minimize the makespan: end of the last task
makespan = model.max();
for (int i = 0; i < nbTasks; ++i) {
makespan.addOperand(model.end(tasks[i]));
}
model.minimize(makespan);
model.close();
// Parameterize the optimizer
optimizer.getParam().setTimeLimit(timeLimit);
optimizer.solve();
}
/*
* Write the solution in a file with the following format:
* - for each operation of each job, the selected machine, the start and end
* dates
*/
public void writeSolution(String fileName) throws IOException {
try (PrintWriter output = new PrintWriter(fileName)) {
System.out.println("Solution written in file " + fileName);
for (int j = 1; j <= nbJobs; ++j) {
for (int o = 1; o <= nbOperations[j - 1]; ++o) {
int taskIndex = jobOperationTask[j - 1][o - 1];
output.write(j + "\t" + o
+ "\t" + taskMachine[taskIndex].getValue()
+ "\t" + tasks[taskIndex].getIntervalValue().getStart()
+ "\t" + tasks[taskIndex].getIntervalValue().getEnd() + "\n");
}
}
}
}
public static void main(String[] args) {
if (args.length < 1) {
System.out.println("Usage: java FlexibleJobshopChangeover instanceFile [outputFile] [timeLimit]");
System.exit(1);
}
String instanceFile = args[0];
String outputFile = args.length > 1 ? args[1] : null;
String strTimeLimit = args.length > 2 ? args[2] : "60";
try (HexalyOptimizer optimizer = new HexalyOptimizer()) {
FlexibleJobshopChangeover model = new FlexibleJobshopChangeover(optimizer);
model.readInstance(instanceFile);
model.solve(Integer.parseInt(strTimeLimit));
if (outputFile != null) {
model.writeSolution(outputFile);
}
} catch (Exception ex) {
System.err.println(ex);
ex.printStackTrace();
System.exit(1);
}
}
}
[1] P. Brandimarte (1993). Routing and scheduling in a flexible job shop by tabu search. Annals of Operations Research 22, 157-183.