Modeling a Real Cable Production System as a Single Machine-Scheduling Problem

2016 ◽  
pp. 327-345
Author(s):  
Sadegh Niroomand ◽  
Béla Vizvári
Keyword(s):  
Production System ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Operating Cost ◽  
Single Machine Scheduling ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Setup Cost ◽  
Total Cost ◽  
Cable Industry

In cases where the size and colour of cable are changed, the cable industry is classified as a multi-product, mass production system. The paper provides a mixed integer linear programming model based on continuous time representation for a case study on the scheduling problem of the cable industry to minimize the total cost including setup cost, operating cost, and inventory holding cost. As the solution methodology, three grouping policies are proposed while Xpress solver could not give any feasible solution for the model. Cables of the same size and the same colour, respectively, of the different types of cable are grouped together. A metaheuristic based on a simulated annealing algorithm is applied to minimize the total cost of proposed solutions. Finally the solution with the smallest total cost is selected as the production schedule of the study case.

scholarly journals Heuristic Algorithms for MapReduce Scheduling Problem with Open-Map Task and Series-Reduce Tasks

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Feifeng Zheng ◽  
Zhaojie Wang ◽  
Yinfeng Xu ◽  
Ming Liu
Keyword(s):  
Numerical Experiments ◽  
Simulated Annealing Algorithm ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Model ◽  
Open Map ◽  
Annealing Algorithm ◽  
Mapreduce Scheduling

Based on the classical MapReduce concept, we propose an extended MapReduce scheduling model. In the extended MapReduce scheduling problem, we assumed that each job contains an open-map task (the map task can be divided into multiple unparallel operations) and series-reduce tasks (each reduce task consists of only one operation). Different from the classical MapReduce scheduling problem, we also assume that all the operations cannot be processed in parallel, and the machine settings are unrelated machines. For solving the extended MapReduce scheduling problem, we establish a mixed-integer programming model with the minimum makespan as the objective function. We then propose a genetic algorithm, a simulated annealing algorithm, and an L-F algorithm to solve this problem. Numerical experiments show that L-F algorithm has better performance in solving this problem.

scholarly journals Berth Scheduling Problem Considering Traffic Limitations in the Navigation Channel

2018 ◽  
Vol 10 (12) ◽  
pp. 4795 ◽  
Author(s):  
Ya Xu ◽  
Kelei Xue ◽  
Yuquan Du
Keyword(s):  
Large Scale ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Container Terminals ◽  
Mixed Integer ◽  
Computational Time ◽  
Scheduling Problem ◽  
Navigation Channel ◽  
Temporary Closure ◽  
Berth Scheduling

In view of the trend of upsizing ships, the physical limitations of natural waterways, huge expenses, and unsustainable environmental impact of channel widening, this paper aims to provide a cost-efficient but applicable solution to improve the operational performance of container terminals that are enduring inefficiency caused by channel traffic limitations. We propose a novel berth scheduling problem considering the traffic limitations in the navigation channel, which appears in many cases including insufficient channel width, bad weather, poor visibility, channel accidents, maintenance dredging of the navigation channel, large vessels passing through the channel, and so on. To optimally utilize the berth and improve the service quality for customers, we propose a mixed-integer linear programming model to formulate the berth scheduling problem under the one-way ship traffic rule in the navigation channel. Furthermore, we develop a more generalized model which can cope with hybrid traffic in the navigation channel including one-way traffic, two-way traffic, and temporary closure of the navigation channel. For large-scale problems, a hybrid simulated annealing algorithm, which employs a problem-specific heuristic, is presented to reduce the computational time. Computational experiments are performed to evaluate the effectiveness and practicability of the proposed method.

A two-agent single-machine scheduling problem to minimize the total cost with release dates

2015 ◽  
Vol 21 (3) ◽  
pp. 805-816 ◽  
Author(s):  
Du-Juan Wang ◽  
Yunqiang Yin ◽  
Wen-Hsiang Wu ◽  
Wen-Hung Wu ◽  
Chin-Chia Wu ◽  
...  
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Release Dates ◽  
Scheduling Problem ◽  
Total Cost

scholarly journals Multi-Period Network Design Problem in Regional Hazardous Waste Management Systems

2019 ◽  
Vol 16 (11) ◽  
pp. 2042 ◽  
Author(s):  
Jun Zhao ◽  
Lixiang Huang
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Programming Model ◽  
Planning Horizon ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Hazardous Wastes ◽  
Total Risk ◽  
Total Cost ◽  
Treatment And Disposal

The management of hazardous wastes in regions is required to design a multi-echelon network with multiple facilities including recycling, treatment and disposal centers servicing the transportation, recycling, treatment and disposal procedures of hazardous wastes and waste residues. The multi-period network design problem within is to determine the location of waste facilities and allocation/transportation of wastes/residues in each period during the planning horizon, such that the total cost and total risk in the location and transportation procedures are minimized. With consideration of the life cycle capacity of disposal centers, we formulate the problem as a bi-objective mixed integer linear programming model in which a unified modeling strategy is designed to describe the closing of existing waste facilities and the opening of new waste facilities. By exploiting the characteristics of the proposed model, an augmented ε -constraint algorithm is developed to solve the model and find highly qualified representative non-dominated solutions. Finally, computational results of a realistic case demonstrate that our algorithm can identify obviously distinct and uniformly distributed representative non-dominated solutions within reasonable time, revealing the trade-off between the total cost and total risk objectives efficiently. Meanwhile, the multi-period network design optimization is superior to the single-period optimization in terms of the objective quality.

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.

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.

scholarly journals A Single-Machine Scheduling Problem with Uncertainty in Processing Times and Outsourcing Costs

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Myoung-Ju Park ◽  
Byung-Cheon Choi
Keyword(s):  
Single Machine ◽  
Operating Cost ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Performance Measure ◽  
Total Weighted Completion Time ◽  
Maximum Deviation ◽  
Scheduling Problem ◽  
Processing Times ◽  
Special Cases

We consider a single-machine scheduling problem with an outsourcing option in an environment where the processing time and outsourcing cost are uncertain. The performance measure is the total cost of processing some jobs in-house and outsourcing the rest. The cost of processing in-house jobs is measured as the total weighted completion time, which can be considered the operating cost. The uncertainty is described through either an interval or a discrete scenario. The objective is to minimize the maximum deviation from the optimal cost of each scenario. Since the deterministic version is known to be NP-hard, we focus on two special cases, one in which all jobs have identical weights and the other in which all jobs have identical processing times. We analyze the computational complexity of each case and present the conditions that make them polynomially solvable.

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