This README.txt file 20200210 was generated by Eduardo Guzman

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GENERAL INFORMATION
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Title: Synthetic input data generator for a MILP model for lot-sizing and scheduling on parallel flexible injection machines with setup common operators

Author Information: 

	Principal Investigator: Beatriz Andres, Universitat Politècnica de València, Plaza Ferrandiz y Carbonell 2 Alcoy (Spain), bandres@cigip.upv.es, ORCID: 0000-0002-7920-7711.
	Associate or Co-investigator: Eduardo Guzman, Universitat Politècnica de València, Plaza Ferrandiz y Carbonell 2 Alcoy (Spain), eguzman@cigip.upv.es, ORCID: 0000-0003-4475-6371.
	Associate or Co-investigator: Raul Poler, Universitat Politècnica de València, Plaza Ferrandiz y Carbonell 2 Alcoy (Spain), rpoler@cigip.upv.es, ORCID: 0000-0003-4475-6371.
	
Date of software: 20200210

Geographic location of data collection: Valencia, Comunidad Valenciana, Spain. 39.46975 -0.37739. 

Information about funding sources or sponsorship that supported the software programming: Universitat Politècnica de València

General description: The Python code generates synthetic input data The dataset contains the input data that for the mathematical model to develop the experiments. Launch LSSP_MILP_BASE_MODEL_GeneratorEXEC for generating synthetic input data by using the CLSD-BPIM Generator. The sizes of the indices (products, parts, resources, periods) for the small, medium and large datasets are the ones used in the experiments.

Keywords: lot-sizing; scheduling; injection moulding; parallel machines; mixed integer linear programming; automotive industry.


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SHARING/ACCESS INFORMATION
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Programming language: Python 3.7

Software license: Apache-2.0

Citation for and links to publications that cite or use the code:
Andres, B., Guzman, E., & Poler, R. (2021). A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators. Complexity, 2021, 1–16. https://doi.org/10.1155/2021/6667516

Links/relationships to previous software: -.

Links to other publicly accessible locations of the software: -.


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NOMENCLATURE
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Python code nomenclature
	Model mathematical notation	
I = i  # Machines
	i Set of machines (indexed by i: i = 1, …, |I|)
J = j  # moulds / tool
	j Set of tools (indexed by j: j = 1, ..., |J|) 
K = k  # components/parts/pieces
	k Set of components/parts/pieces (indexed by k: k = 1, …, |K|)
L = l  # Index setup type operators
	l Set of setup type operators (indexed by l: l = 1, …, |L|)
T = t  # Periods
	t Set of time periods (indexed by t: t = 1, …, |T|)
Machines
	i Set of machines (indexed by i: i = 1, …, |I|)
Tools
	j Set of tools (indexed by j: j = 1, ..., |J|) 
Parts
	k Set of components/parts/pieces (indexed by k: k = 1, …, |K|)
type_operators
	l Set of setup type operators (indexed by l: l = 1, …, |L|)
Periods
	t Set of time periods (indexed by t: t = 1, …, |T|)
Amount_tools
	aj	Total amount of tools j available for production
Backorder_cost
	cbk	Backorder cost of product k 
Inventory_cost
	cik	Inventory cost of product k
Stock_coverage
	covkt	Stock coverage defined as number of time periods for the stock minimum coverage of product k during time period t
Setup_cost_tool
	crij	Setup cost of tool j on machine i
Setup_cost_preparing_tool
	csj	Setup cost of preparing tool j
Coverage_stockout
	cstk	Coverage stockout cost of product k
Demand_product 
	dkt	Demand of product k during time period t
Initial_inventory
	INVk0	Initial inventory of product k
Maximum_inventory
	INVMAXk	Maximum inventory units for product k during time period t
Minimum_inventory
	INVMINk	Minimum inventory units for product k during time period t
tool_changes
	nct	Amount of tool changes allowed during time period t
products_no_longer_produced
	npjk	Amount of products k no longer produced when tool j is set up
products_produced
	pjk	Amount of products k produced when tool j is set up
Route
	rij	1 if tool j can be set up on machine i, 0 otherwise
Production_time
	tpt	Production time available during time period t 
Number_setup_operators
	slailj	Number of setup type operators l required to setup the tool j on machine i
Cost_type_operator
	sclilj	Cost of type operator l to setup the tool j on machine i
available_workers
	slsl	Number of available workers of type operator l available