Production Scheduling in a Flexible Hybrid Flow Shop in the Food Industry Based on the Theory of Constraints

2021 ◽  
Vol 52 ◽  
pp. 124-136
Author(s):  
Adel Mendoza-Mendoza ◽  
Wilfrido Ospino-Castro ◽  
Daniela Romero-Martínez
Keyword(s):  
Mathematical Model ◽  
Production Scheduling ◽  
Flow Shop ◽  
Flow Line ◽  
Theory Of Constraints ◽  
Mixed Integer ◽  
Hybrid Flow Shop ◽  
Timely Response ◽  
Integer Linear Model ◽  
The Mathematical Model

This paper proposes a mathematical model for production scheduling, whose objective is to maximize the profits or Throughput of a company in the food sector through a Flexible Hybrid Flow, based on the theory of constraints. Considering the company's production configuration, which is a two-stage hybrid flow line, a mixed integer linear model programming (MILP) was formulated and programmed to adequately represent the real situation. The mathematical model developed in this study that is an easy and effective tool that helps to control the production process, by optimizing the quantities of each product to be produced, as well as establishing the sequence in which they must be carried out, which becomes an advantage against its competitors and also obtain a timely response to the needs of demand and compliance with the commitments made to its customers. The results obtained with the MILP, with reasonable computational times, allow for maximizing profits, considering the constraints of the problem.

Lot Streaming and Preventive Maintenance in a Multiple Product Permutation Flow Shop with Intermingling

2014 ◽  
Vol 564 ◽  
pp. 689-693 ◽  
Author(s):  
Navid Mortezaei ◽  
Zulkifli Norzima ◽  
S.H. Tang ◽  
Mohd Yusuff Rosnah
Keyword(s):  
Mathematical Model ◽  
Preventive Maintenance ◽  
Flow Shop ◽  
Mixed Integer ◽  
Programming Formulation ◽  
Lot Streaming ◽  
Proposed Model ◽  
Permutation Flow Shop ◽  
Integer Linear Model ◽  
Multiple Product

A mathematical model forlot streaming problem with preventive maintenance was proposed. A mixed-integer linear model for multiple-product lot streaming problems was also developed. Mixed-integer programming formulation was presented which will enable the user to identify optimal sublot sizes and sequences simultaneously. Two situations were considered:1) all machines were available, and 2) all machines needed preventive maintenance tasks. For both situations a new mixed-integer formulation was developed. To demonstrate the practicality of the proposed model, numerical example was used. It showed that the percentage of make span reduction due to lot streaming in permutation flow shop is 54% when compared to consistent sublots with intermingling case.

scholarly journals An Optimized Mathematical Model for Items Supplies Planning of a Logistic System

2016 ◽  
Vol 10 (10) ◽  
pp. 133
Author(s):  
Mohammad Ali Nasiri Khalili ◽  
Mostafa Kafaei Razavi ◽  
Morteza Kafaee Razavi
Keyword(s):  
Mathematical Model ◽  
Mixed Integer ◽  
Logistics System ◽  
Proposed Model ◽  
Multiple Objective Decision Making ◽  
System Requirements ◽  
Purchasing Logistics ◽  
The Cost ◽  
The Mathematical Model ◽  
First Time

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.

scholarly journals Sustainable Scheduling of the Production in the Aluminum Furnace Hot Rolling Section with Uncertain Demand

2021 ◽  
Vol 13 (14) ◽  
pp. 7708
Author(s):  
Yiping Huang ◽  
Qin Yang ◽  
Jinfeng Liu ◽  
Xiao Li ◽  
Jie Zhang
Keyword(s):  
Hot Rolling ◽  
Production Scheduling ◽  
Demand Uncertainty ◽  
Flow Shop ◽  
Operation Time ◽  
Decision Time ◽  
Scenario Tree ◽  
Mixed Integer ◽  
Rolling Horizon ◽  
The Sustainable Development

In order to reduce the energy consumption of furnaces and save costs in the product delivery time, the focus of this paper is to discuss the uncertainty of demand in the rolling horizon and to globally optimize the sustainability of the production in the aluminum furnace hot rolling section in environmental and economic dimensions. First, the triples α/β/γ are used to describe the production scheduling in the aluminum furnace hot rolling section as the scheduling of flexible flow shop, satisfied to constraints of demand uncertainty, operation logic, operation time, capacity and demand, objectives of minimizing the residence time of the ingot in the furnace and minimizing the makespan. Second, on the basis of describing the uncertainty of demand in rolling horizon with the scenario tree, a multi-objective mixed integer linear programming (MILP) optimization model for sustainable production in the aluminum furnace hot rolling section is formulated. Finally, an aluminum alloy manufacturer is taken as an example to illustrate the proposed model. The computational results show that when the objective weight combination takes the value of α=0.7, β=0.3, the sustainability indicators of the environmental and economic dimensions can be optimized to the maximum extent possible at the same time. Increasingly, managerial suggestions associated with the trade-off between environmental and economic dimensions are presented. Scheduling in the rolling horizon can optimize the production process of the aluminum furnace hot rolling section globally, indicating that it is more conducive to the sustainable development of the environment and economic dimensions than scheduling in a single decision time period.

scholarly journals Integration of Lot Sizing and Flow Shop Scheduling with Lot Streaming

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Navid Mortezaei ◽  
Norzima Zulkifli
Keyword(s):  
Flow Shop ◽  
Lot Sizing ◽  
Flow Shop Scheduling ◽  
Mixed Integer ◽  
Lot Streaming ◽  
Optimal Sequence ◽  
Shop Scheduling ◽  
Proposed Model ◽  
Integer Linear Model ◽  
No Wait

We will develop a mathematical model for the integration of lot sizing and flow shop scheduling with lot streaming. We will develop a mixed-integer linear model for multiple products lot sizing and lot streaming problems. Mixed-integer programming formulation is presented which will enable the user to find optimal production quantities, optimal inventory levels, optimal sublot sizes, and optimal sequence simultaneously. We will use numerical example to show practicality of the proposed model. We test eight different lot streaming problems: (1) consistent sublots with intermingling, (2) consistent sublots and no intermingling between sublots of the products (without intermingling), (3) equal sublots with intermingling, (4) equal sublots without intermingling, (5) no-wait consistent sublots with intermingling, (6) no-wait equal sublots with intermingling, (7) no-wait consistent sublots without intermingling, and (8) no-wait equal sublots without intermingling. We showed that the best makespan can be achieved through the consistent sublots with intermingling case.

A New Mathematical Model for Hybrid Flow Shop Under Time-Varying Resource and Exact Time-Lag Constraints

2021 ◽  
pp. 87-99
Author(s):  
Quoc Nhat Han Tran ◽  
Nhan Quy Nguyen ◽  
Hicham Chehade ◽  
Farouk Yalaoui ◽  
Frédéric Dugardin
Keyword(s):  
Mathematical Model ◽  
Flow Shop ◽  
Time Lag ◽  
Hybrid Flow Shop ◽  
Time Varying ◽  
Exact Time

Energy-efficient multi-objective scheduling algorithm for hybrid flow shop with fuzzy processing time

2019 ◽  
Vol 233 (10) ◽  
pp. 1282-1297 ◽  
Author(s):  
Binghai Zhou ◽  
Wenlong Liu
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Processing Time ◽  
Flow Shop ◽  
Scheduling Algorithm ◽  
Mixed Integer ◽  
Computational Time ◽  
Hybrid Flow Shop ◽  
Multi Objective ◽  
Fuzzy Processing Time

Increasing costs of energy and environmental pollution is prompting scholars to pay close attention to energy-efficient scheduling. This study constructs a multi-objective model for the hybrid flow shop scheduling problem with fuzzy processing time to minimize total weighted delivery penalty and total energy consumption simultaneously. Setup times are considered as sequence-dependent, and in-stage parallel machines are unrelated in this model, meticulously reflecting the actual energy consumption of the system. First, an energy-efficient bi-objective differential evolution algorithm is developed to solve this mixed integer programming model effectively. Then, we utilize an Nawaz-Enscore-Ham-based hybrid method to generate high-quality initial solutions. Neighborhoods are thoroughly exploited with a leader solution challenge mechanism, and global exploration is highly improved with opposition-based learning and a chaotic search strategy. Finally, problems in various scales evaluate the performance of this green scheduling algorithm. Computational experiments illustrate the effectiveness of the algorithm for the proposed model within acceptable computational time.

scholarly journals Comparing Mixed-Integer Programming and Constraint Programming Models for the Hybrid Flow Shop Scheduling Problem with Dedicated Machines

2021 ◽  
Vol 54 (4) ◽  
pp. 591-597
Author(s):  
Asma Ouled Bedhief
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Constraint Programming ◽  
Flow Shop ◽  
Programming Model ◽  
Flow Shop Scheduling ◽  
Mixed Integer ◽  
Hybrid Flow Shop ◽  
Dedicated Machines ◽  
Hybrid Flow Shop Scheduling

The paper considers a two-stage hybrid flow shop scheduling problem with dedicated machines and release dates. Each job must be first processed on the single machine of stage 1, and then, the job is processed on one of the two dedicated machines of stage 2, depending on its type. Moreover, the jobs are available for processing at their respective release dates. Our goal is to obtain a schedule that minimizes the makespan. This problem is strongly NP-hard. In this paper, two mathematical models are developed for the problem: a mixed-integer programming model and a constraint programming model. The performance of these two models is compared on different problem configurations. And the results show that the constraint programming outperforms the mixed-integer programming in finding optimal solutions for large problem sizes (450 jobs) with very reasonable computing times.

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