Simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines

Copyright © 2014 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 31 January 2014, available online: http://www.tandfonline.com/10.1080/00207543.2013.879618Growing interests from customers in customised products and increasing competitions among peers necessitate companies to configure their manufacturing systems more effectively than ever before. We propose a new assembly line system configuration for companies that need intelligent solutions to satisfy customised demands on time with existing resources. A mixed-model parallel two-sided assembly line system is introduced based on the parallel two-sided assembly line system previously proposed by Ozcan et al. (Balancing parallel two-sided assembly lines, International Journal of Production Research, 48 (16), 4767-4784, 2010). The mixed-model parallel two-sided assembly line balancing problem is illustrated with examples from the perspective of simultaneous balancing and sequencing. An agent based ant colony optimisation algorithm is proposed to solve the problem. This algorithm is the first attempt in the literature to solve an assembly line balancing problem with an agent based ant colony optimisation approach. The algorithm is illustrated with an example and its operational procedures and principles explained and discussed

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Improvement of Work Process Performance with Task Assignments and Mental Workload Balancing

The outcome of a work process depends heavily on which tasks assigned to which employees. However, sometimes-optimized assignments based on employees’ qualifications may result in an uneven and ineffective workload distribution among them. Likewise, an even workload distribution without considering the employee\u27s qualifications may cause unproductive employee-task matching that results in low performance of employees. This trade-off is even more noticeable for work processes during critical time junctions, such as in military command centers and emergency rooms that require being fast and effective without making errors. This study proposes that optimizing task-employee assignments according to their capabilities while also keeping them under a workload threshold, results in better performance for work processes, especially during critical time junctions. The goal is to select the employee-task assignments in order to minimize the average duration of a work process while keeping the employees under a workload threshold to prevent errors caused by overload. Due to uncertainties inherent in the problem related with the inter-arrival time of work orders, task durations and employees\u27 instantaneous workload, a utilized simulation-optimization approach solves this problem. More specifically, a discrete event human performance simulation model evaluates the objective function of the problem coupled with a genetic algorithm based meta-heuristic optimization approach to search the solution space. This approach proved to be useful in determining the right task-agent assignments by taking into consideration the employees\u27 qualifications and mental workload in order to minimize the average duration of a work process. Use of a sample work process shows the effectiveness of the developed simulation-optimization approach. Numerical tests indicate that the proposed approach finds better solutions than common practices and other simulation-optimization methods. Accordingly, by using this method, organizations can increase performance, manage excess-level workloads, and generate higher satisfactory environments for employees, without modifying the structure of the process itself

Multi-Period Stochastic Resource Planning: Models, Algorithms and Applications

This research addresses the problem of sequential decision making in the presence of uncertainty in the professional service industry. Specifically, it considers the problem of dynamically assigning resources to tasks in a stochastic environment with both the uncertainty of resource availability due to attrition, and the uncertainty of job availability due to unknown project bid outcome. This problem is motivated by the resource planning application at the Hewlett Packard (HP) Enterprises. The challenge is to provide resource planning support over a time horizon under the influence of internal resource attrition and demand uncertainty. To ensure demand is satisfied, the external contingent resources can be engaged to make up for internal resource attrition. The objective is to maximize profitability by identifying the optimal mix of internal and contingent resources and their assignments to project tasks under explicit uncertainty. While the sequential decision problems under uncertainty can often be modeled as a Markov decision process (MDP), the classical dynamic programming (DP) method using the Bellman’s equation suffers the well-known curses-of-dimensionality and only works for small size instances. To tackle the challenge of curses-of-dimensionality this research focuses on developing computationally tractable closed-loop Approximate Dynamic Programming (ADP) algorithms to obtain near-optimal solutions in reasonable computational time. Various approximation schemes are developed to approximate the cost-to-go function. A comprehensive computational experiment is conducted to investigate the performance and behavior of the ADP algorithm. The performance of ADP is also compared with that of a rolling horizon approach as a benchmark solution. Computational results show that the optimization model and algorithm developed in this thesis are able to offer solutions with higher profitability and utilization of internal resource for companies in the professional service industry

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

A Survey on Cost and Profit Oriented Assembly Line Balancing

http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac2014/media/files/0866.pdfInternational audienceProblems, approaches and analytical models on assembly line balancing that deal explicitly with cost and profit oriented objectives are analysed. This survey paper serves to identify and work on open problems that have wide practical applications. The conclusions derived might give insights in developing decision support systems (DSS) in planning profitable or cost efficient assembly lines