scholarly journals Integrated Production-Distribution Scheduling Problem with Multiple Independent Manufacturers

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Jianhong Hao ◽  
Lisi Cao ◽  
Dakui Jiang
Keyword(s):  
Public Service ◽  
Parallel Machines ◽  
Programming Model ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Production Schedule ◽  
Integrated Production ◽  
Batch Delivery ◽  
Distribution Scheduling ◽  
Production Distribution

We consider the nonstandard parts supply chain with a public service platform for machinery integration in China. The platform assigns orders placed by a machinery enterprise to multiple independent manufacturers who produce nonstandard parts and makes production schedule and batch delivery schedule for each manufacturer in a coordinate manner. Each manufacturer has only one plant with parallel machines and is located at a location far away from other manufacturers. Orders are first processed at the plants and then directly shipped from the plants to the enterprise in order to be finished before a given deadline. We study the above integrated production-distribution scheduling problem with multiple manufacturers to maximize a weight sum of the profit of each manufacturer under the constraints that all orders are finished before the deadline and the profit of each manufacturer is not negative. According to the optimal condition analysis, we formulate the problem as a mixed integer programming model and use CPLEX to solve it.

scholarly journals Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Wenming Cheng ◽  
Peng Guo ◽  
Zeqiang Zhang ◽  
Ming Zeng ◽  
Jian Liang
Keyword(s):  
Variable Neighborhood Search ◽  
Parallel Machines ◽  
Programming Model ◽  
Search Algorithm ◽  
Optimal Schedule ◽  
Deteriorating Jobs ◽  
Mixed Integer ◽  
Computational Time ◽  
Neighborhood Search ◽  
Scheduling Problem

In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.

Coordinating lot sizing and integrated production and distribution scheduling with batch delivery and holding cost

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maedeh Bank ◽  
Mohammad Mahdavi Mazdeh ◽  
Mahdi Heydari ◽  
Ebrahim Teimoury
Keyword(s):  
Supply Chain ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Time Interval ◽  
Content Type ◽  
Integrated Production ◽  
Holding Costs ◽  
Integrated Production And Distribution ◽  
Distribution Scheduling ◽  
Production And Distribution

PurposeThe aim of this paper is to present a method for finding the optimum balance between sequence-dependent setup costs, holding costs, delivery costs and delay penalties in an integrated production–distribution system with lot sizing decisions.Design/methodology/approachTwo mixed integer linear programming models and an optimality property are proposed for the problem. Since the problem is NP-hard, a genetic algorithm reinforced with a heuristic is developed for solving the model in large-scale settings. The algorithm parameters are tuned using the Taguchi method.FindingsThe results obtained on randomly generated instances reveal a performance advantage for the proposed algorithm; it is shown that lot sizing can reduce the average cost of the supply chain up to 11.8%. Furthermore, the effects of different parameters and factors of the proposed model on supply chain costs are examined through a sensitivity analysis.Originality/valueAlthough integrated production and distribution scheduling in make-to-order industries has received a great deal of attention from researchers, most researchers in this area have treated each order as a job processed in an uninterrupted time interval, and no temporary holding costs are assumed. Even among the few studies where temporary holding costs are taken into consideration, none has examined the effect of splitting an order at the production stage (lot sizing) and the possibility of reducing costs through splitting. The present study is the first to take holding costs into consideration while incorporating lot sizing decisions in the operational production and distribution problem.

Single machine earliness/tardiness scheduling problem with grey processing times and the grey common due date

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oğuzhan Ahmet Arık
Keyword(s):  
Programming Model ◽  
Heuristic Method ◽  
Mixed Integer ◽  
Grey Theory ◽  
Scheduling Problem ◽  
Due Date ◽  
Content Type ◽  
Common Due Date ◽  
Processing Times ◽  
Uncertainty Of Parameters

PurposeThis paper presents a mixed-integer programming model for a single machine earliness/tardiness scheduling problem where the objective is to minimize total earliness/tardiness duration when the uncertainty of parameters such as processing times and due date is coded with grey numbers.Design/methodology/approachGrey theory and grey numbers are used for illustrating the uncertainty of parameters in processing times and common due date, where the objective is to minimize the total earliness/tardiness duration. The paper proposes a 0–1 mathematical model for the problem and an effective heuristic method for the problem by using expected processing times for ordering jobs.FindingsThe uncertainty of the processing times and common due date are encoded with grey numbers and a position-dependent mixed-integer mathematical programming model is proposed for the problem in order to minimize total grey earliness/tardiness duration of jobs having grey processing times and a common due date. By using expected processing times for ranking grey processing times, V-shaped property of the problem and an efficient heuristic method for the problem are proposed. Solutions obtained from the heuristic method show that the heuristic is effective. The experimental study also reveals that while differences between upper and lower bounds of grey processing times decrease, the proposed heuristic's performance decreases.Originality/valueThe grey theory and grey numbers have been rarely used as machine scheduling problems. Therefore, this study provides an important contribution to the literature.

scholarly journals Coordinated Production Planning and Scheduling Problem in a Foundry

2017 ◽  
Vol 17 (3) ◽  
pp. 133-138
Author(s):  
A. Stawowy ◽  
J. Duda
Keyword(s):  
Production Planning ◽  
Programming Model ◽  
Mixed Integer ◽  
Medium Size ◽  
Scheduling Problem ◽  
Planning And Scheduling ◽  
Alloy Casting ◽  
Production Planning And Scheduling ◽  
Multiple Cores ◽  
Molding Shop

Abstract In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data simulating actual production parameters in one of the medium size foundry.

scholarly journals Integrated day-ahead energy procurement and production scheduling

2018 ◽  
Vol 66 (11) ◽  
pp. 950-963 ◽  
Author(s):  
Egidio Leo ◽  
Sebastian Engell
Keyword(s):  
Production Scheduling ◽  
Programming Model ◽  
Production Capacity ◽  
Electricity Consumption ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Production Schedule ◽  
Sources Of Uncertainty ◽  
Continuous Power ◽  
The Cost

Abstract For the optimal operation of power-intensive plants, a challenge which is addressed in this work is to simultaneously determine the optimal production schedule and the optimal day-ahead electricity commitment. In order to ensure stability of the power grid, the electricity suppliers impose a daily electricity commitment to large consumers. The consumers have to commit one day in advance to the amount of energy they are going to purchase and use for a horizon of 24 hours (with an hourly discretization) and in case the actual electricity consumption differs significantly from the committed profile, the consumer is obliged to pay penalties. Since the consumers have to commit to the electricity suppliers before the actual electricity demand is known, uncertainty needs to be taken into account. A stochastic mixed-integer linear programming model is developed to consider two critical sources of uncertainty: equipment breakdowns and deviation prices. Equipment breakdowns can reduce the production capacity and make the actual electricity consumption deviate from the day-ahead electricity commitment. The application of the proposed approach to a continuous power-intensive plant shows the benefit gained from the solution of the stochastic model instead of the deterministic counterpart in terms of reduction of the cost of the energy.

Integrated Scheduling Optimization of Handling Operations in Container Terminal

2013 ◽  
Vol 380-384 ◽  
pp. 4775-4781
Author(s):  
Ji Feng Qian ◽  
Xiao Ning Zhu ◽  
Zhan Dong Liu
Keyword(s):  
Approximate Solution ◽  
Programming Model ◽  
Container Terminal ◽  
Mixed Integer ◽  
Operating Efficiency ◽  
Container Ship ◽  
Scheduling Problem ◽  
Scheduling Optimization ◽  
Integrated Scheduling ◽  
Different Types

In order to improve the efficiency of the handling operations equipment in container terminal, reduce the waiting time of container ship in Port, this paper researches the integrated scheduling of the different types of handling equipment in container terminal, considers the constraints of different handling equipment impact between each other, build a mixed integer programming model, presents a heuristic algorithm for the of the scheduling problem and gets the approximate solution. The results show that the integrated scheduling can effectively reduce the time of the ship staying in port, and improve the overall operating efficiency of the port.

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