Search query: hoist schedule problem  pollution

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abstract: Hoist scheduling in automated electroplating lines has been extensively studied in a static environment. However, practical electroplating lines are subject to diversified unforeseen disruptions that require frequent rescheduling to maintain or optimize system performance. This paper addresses a hoist scheduling problem, where randomly arriving jobs need to be inserted into an existing schedule without changing the sequence of hoist moves already scheduled. The objective is to minimize the total completion time of all the jobs in the existing schedule and a newly inserted job. We develop a polynomial time heuristic that adjusts the starting times of the existing hoist moves to a limited extent but does not bring about a severe disturbance of the existing hoist moves. We compare our algorithm with two existing approaches with different rescheduling policies (i.e. partial and zero adjustment of the existing schedule) We empirically analyze the productivity and the stability of the schedules generated by the three approaches. Computational results demonstrate that our algorithm can generate more productive and stable schedules than the two existing approaches. Note to Practitioners Electroplating and chemical surface treatment lines with automated material handling hoists are commonplace in electronics, semiconductor, and many other manufacturing industries. In an uncertain environment, hoist rescheduling plays an important role in improving the productivity and reducing the impact of disruptions. This paper presents a hoist scheduling algorithm to deal with dynamic job arrivals by considering the impact of the disturbance incurred by rescheduling. Our algorithm can generate a better schedule with smaller total completion time and slighter disturbance than the existing algorithms. The proposed algorithm runs in polynomial time and can be used to control hoist operations in practical electroplating lines. A comparative analysis provides useful insights on the implementation of rescheduling approaches and policies to industry practitioners.
author_names: Pengyu Yan

Ada Che

Eugene Levner

Shi Qiang Liu
title: A Heuristic for Inserting Randomly Arriving Jobs Into an Existing Hoist Schedule
venue: IEEE Transactions on Automation Science and Engineering
year: 2018

abstract: The cyclic hoist scheduling problem (CHSP) is a well studied optimisation problem due to its importance in industry. Despite the wide range of solving techniques applied to the CHSP and its variants, the models have remained complicated and inflexible, or have failed to scale up with larger problem instances. This article re examines modelling of the CHSP and proposes a new simple, flexible constraint programming formulation. We compare current state of the art solving technologies on this formulation, and show that modelling in a high level constraint language, MiniZinc, leads to both a simple, generic model and to computational results that outperform the state of the art. We further demonstrate that combining integer programming and lazy clause generation, using the multiple cores of modern processors, has potential to improve over either solving approach alone.
author_names: Mark Wallace

N Yorke-Smith
title: A new constraint programming model and solving for the cyclic hoist scheduling problem
venue: Constraints An Int. J.
year: 2020

abstract: The Hoist Scheduling Problem is combinatory, so tools such as mathematical programming need to be used to get the sequence of movements, respecting the constraints of the process by minimizing the cycle time. A sequence in which the order of movements follows the order of the process is known as the basic diagram. These schedules do not have any clearance for the hoist to make any other movements, resulting in a loss in productivity. This chapter takes the production line of a Mexican factory as a case study, analyzing the hoist's travelling speed to find sequences of movements that could improve productivity. The results of the study indicate that the cycle time has a nonlinear behavior in respect of the hoist's travelling speed and it was determined that there are travelling speeds for which sequences are obtained with enough clearance to make other movements and keep other carriers on the line. A suitable speed was estimated in the case. An Analysis of the Traveling Speed in the Traveling Hoist Scheduling Problem for Electroplating Processes
author_names: Jose Itzcoatl Gomar-Madriz

Salvador Hernandez-Gonzalez

J Navarrete-Damian
title: An Analysis of the Traveling Speed in the Traveling Hoist Scheduling Problem for Electroplating Processes
year: 2020

abstract: Electroplating facilities often face the Cyclic Hoist Scheduling Problem when a repetitive sequence of moves is searched for the hoists. This paper addresses this optimization problem extended to the design of the workshop, where we aim to minimize both the cycle time and the number of hoists used. For this goal, we propose a genetic meta heuristic approach which introduces a novel solution encoding to enlarge the solutions' search space. Our encoding procedure is based on hoists' empty moves, and includes separator characters. With the latter, we obtain solutions that were not reachable by previous approaches. Each solution obtained thanks to the genetic operators is evaluated by using a Mixed Integer Linear Program. This one checks the constraints of the problem (such as capacity constraints and soaking time bounds) and computes the smallest cycle time for a given moving sequence and its associated number of hoists. Some results are presented using benchmark instances for which our approach allows to improve the best known solutions.
author_names: Laajili Emna

Lamrous Sid

Manier Marie-Ange

Nicod Jean-Marc
title: Genetic Algorithm Based Approach for the Multi Hoist Design and Scheduling Problem
venue: 2019 International Conference on Industrial Engineering and Systems Management (IESM)
year: 2019

abstract: In this paper, we propose a Mixed Integer Linear Programming model for solving a hoist scheduling problem with several transportation resources. This model complements initial work that neglected the risk of collisions between hoists. This new model identifies and manages the various possible collision situations, and it is intended to be integrated as a solution evaluation module in a hybrid algorithm addressing the broader and more complex joint problem of sizing transport resources and scheduling surface treatment workshops. In this global approach, an evolutionary algorithm first generates partially feasible solutions, whose total feasibility is then verified a posteriori, thanks to the proposed new model. This model is validated through tests performed on instances of the literature.
author_names: Emna Laajili

Sid Lamrous

Marie-Ange Manier

Jean Marc Nicod
title: Collision Free Based Model for the Cyclic Multi Hoist Scheduling Problem
venue: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
year: 2019

abstract: The current paper deals with the cyclic multi hoist scheduling problem in electroplating lines considering rentrance. Identical parts are produced with processing time windows. Moreover, re entrance is also considered. These together make it more challenged to obtain better schedules improving the productivity. To achieve this, multi degree cycles are considered. To our best knowledge, this is the first research in this generally complicated scenario. In order to maximize the productivity of the production line, i.e. minimize the cycle time for a given degree, operations of hoists are first analyzed in detail to avoid their collision. Then, operations related the re entrance are modeled. Based on these work, a mixed integer linear programming model is proposed. An industrial instances is used to test the proposed model. It is solved using the commercial software ILOG CPLEX. Results illustrate the efficiency of the proposed approach.
author_names: Xin Li

Yanchun Pan

Richard Y K Fung
title: Optimal Scheduling of the Reentrant Multi Degree Cyclic Multi Hoist Scheduing Problem
venue: 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
year: 2019

abstract: Abstract The pollution routing problem aims to route a number of vehicles and determines their speeds on each route segment to minimize total cost, including fuel, emission and driver costs. Recently, carbon pricing initiatives have been widely implemented worldwide. With consideration of the interactions between carbon pricing initiatives and freight schedules, this paper presents a carbon pricing initiatives based bi level pollution routing problem involving an authority and a freight company. An interactive solution approach integrating a fuzzy logic controlled particle swarm optimization and a modified adaptive large neighborhood search heuristic is designed to search for solutions for the carbon pricing initiatives based bi level pollution routing problem. Computational experiments and analysis are then conducted to shed light on the influence of carbon pricing initiatives on carbon emissions and the total cost of freight companies. In this part, extended models for the carbon pricing initiatives based bi level pollution routing problem with a freight company delivering to multiple regions and with multiple freight companies are proposed and computed using the algorithms based on the interactive solution approach. The results indicate that the proposed method can promote freight company improvements in emission performance, and assist authorities in making decisions for road freight transport carbon emission reduction.
author_names: Rui Qiu

Jiuping Xu

Ruimin Ke

Ziqiang Zeng

Yinhai Wang
title: Carbon pricing initiatives based bi level pollution routing problem
venue: Eur. J. Oper. Res.
year: 2020

abstract: Abstract The hybrid flowshop scheduling problem (HFSP) has been widely studied in the past decades. The most commonly used criterion is production efficiency. Green criteria, such as energy consumption and carbon emission, have attracted growing attention with the improvement of the environment protection awareness. Limited attention has been paid to noise pollution. However, noise pollution can lead to health and emotion disorder. Thus, this paper studies a multi objective HFSP considering noise pollution in addition to production efficiency and energy consumption. First, we formulate a new mixed integer programming model for this multi objective HFSP. To realize the green scheduling, one energy conservation/noise reduction strategy is embedded into this model. Then, a novel multi objective cellular grey wolf optimizer (MOCGWO) is proposed to address this problem. The proposed MOCGWO integrates the merits of cellular automata (CA) for diversification and variable neighborhood search (VNS) for intensification, which balances exploration and exploitation. Finally, to validate the efficiency and effectiveness of the proposed MOCGWO, we compare our proposal with other well known multi objective evolutionary algorithms by conducting comparison experiments. The experimental results show that the proposed MOCGWO is significantly better than its competitors on this problem.
author_names: Chao Lu

Liang Gao

Quanke Pan

Xinyu Li

Jun Zheng
title: A multi objective cellular grey wolf optimizer for hybrid flowshop scheduling problem considering noise pollution
venue: Appl. Soft Comput.
year: 2019

abstract: Many optimization algorithms have been proposed to solve hybrid flowshop scheduling problem (HFSP) However, with the development of industry and society, labor right and labor safety have become important problem to consider in production scheduling. So the green HFSP considering makespan, noise and dust pollution becomes an urgent problem to be solved. In this paper, the rider optimization algorithm (ROA) is modified into the multi objective rider optimization algorithm (MOROA) using Pareto archive and neighborhood sorting techniques. The Pareto archive and neighborhood sorting technology make the Pareto optimal solution set of MOROA have higher coverage and more solutions. Then MOROA is discretized into discrete MOROA (DMOROA) to solve the HFSP considering makespan, noise and dust pollution. DMOROA is tested on 10, 30 and 50 jobs HFSP considering makespan, noise and dust pollution. The test results are compared with two multi objective algorithms to verify the performance of DMOROA. And the test results verify that the DMOROA is superior to the comparison algorithms in search accuracy, number of non dominated solutions, diversity of solution set and stability. Therefore, DMOROA is effective in solving multi objective HFSP considering makespan, noise and dust pollution.
author_names: Yanming Fu

Zhuohang Li

Ningjiang Chen

Chiwen Qu
title: A Discrete Multi Objective Rider Optimization Algorithm for Hybrid Flowshop Scheduling Problem Considering Makespan, Noise and Dust Pollution
venue: IEEE Access
year: 2020

abstract: This paper deals with the robust optimization for the cyclic hoist scheduling problem with processing time window constraints. The robustness of a cyclic hoist schedule is defined as its ability to remain stable in the presence of perturbations or variations of certain degree in the hoist transportation times. With such a definition, we propose a method to measure the robustness of a cyclic hoist schedule. A bi objective mixed integer linear programming (MILP) model, which aims to optimize cycle time and robustness, is developed for the robust cyclic hoist scheduling problem. We prove that the optimal cycle time is a strictly increasing function of the robustness and the problem has infinite Pareto optimal solutions. Furthermore, we derive the so called ideal point and nadir point that define the lower and upper bounds for the objective values of Pareto front. A Pareto optimal solution can be obtained by solving a single objective MILP model to minimize the cycle time for a given value of robustness or maximize the robustness for a specific cycle time. The single objective MILP models are solved using commercial optimization software CPLEX. Computational results on several benchmark instances and randomly generated instances indicate that the proposed approach can solve large scale problems within a reasonable amount of time.
author_names: Ada Che

Jianguang Feng

Haoxun Chen

Chengbin Chu
title: Robust optimization for the cyclic hoist scheduling problem
venue: Eur. J. Oper. Res.
year: 2015