http://egon.cheme.cmu.edu/Papers/BatchReviewMendezGrossmann.pdf

State-of-the-art review of optimization methods for short-term scheduling of batch processes

https://link.springer.com/content/pdf/10.1007/978-3-642-78910-6_43.pdf

The Job Shop Scheduling Problem: Conventional and new Solution Techniques

Manufacturing process planning is the process of selecting and sequencing manufacturing processes such that they achieve one or more goals and satisfy a set of domain constraints. Manufacturing scheduling is the process of selecting a process plan and assigning manufacturing resources for specific time periods to the set of manufacturing processes in the plan. It is, in fact, an optimization process by which limited manufacturing resources are allocated over time among parallel and sequential activities. Manufacturing process planning and scheduling are usually considered to be two separate and distinct phases. Traditional optimization approaches to these problems do not consider the constraints of both domains simultaneously and result in suboptimal solutions. Without considering real-time machine workloads and shop floor dynamics, process plans may become suboptimal or even invalid at the time of execution. Therefore, there is a need for the integration of manufacturing process-planning and scheduling systems for generating more realistic and effective plans. After describing the complexity of the manufacturing process-planning and scheduling problems, this paper reviews the research literature on manufacturing process planning, scheduling as well as their integration, particularly on agent-based approaches to these difficult problems. Major issues in these research areas are discussed, and research opportunities and challenges are identified

/pdf/agent-based-distributed-manufacturing-process-planning-and-2kdn4qr5cl.pdf

Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey

Grid computing is becoming a mainstream technology for large-scale distributed resource sharing and system integration. Workflow management is emerging as one of the most important grid services. In this work, a workflow management system for grid computing, called GridFlow, is presented, including a user portal and services of both global grid workflow management and local grid sub-workflow scheduling. Simulation, execution and monitoring functionalities are provided at the global grid level, which work on top of an existing agent-based grid resource management system. At each local grid, sub-workflow scheduling and conflict management are processed on top of an existing performance prediction based task scheduling system. A fuzzy timing technique is applied to address new challenges of workflow management in a cross-domain and highly dynamic grid environment. A case study is given and corresponding results indicate that local and global grid workflow management can coordinate with each other to optimise workflow execution time and solve conflicts of interest.

/pdf/gridflow-workflow-management-for-grid-computing-42ikwh16cv.pdf

GridFlow: workflow management for grid computing

Owing to its inherent modeling flexibility, simulation is often regarded as the proper means for supporting decision making on supply chain design. The ultimate success of supply chain simulation, however, is determined by a combination of the analyst's skills, the chain members' involvement, and the modeling capabilities of the simulation tool. This combination should provide the basis for a realistic simulation model, which is both transparent and complete. The need for transparency is especially strong for supply chains as they involve (semi)autonomous parties each having their own objectives. Mutual trust and model effectiveness are strongly influenced by the degree of completeness of each party's insight into the key decision variables. Ideally, visual interactive simulation models present an important communicative means for realizing the required overview and insight. Unfortunately, most models strongly focus on physical transactions, leaving key decision variables implicit for some or all of the parties involved. This especially applies to control structures, that is, the managers or systems responsible for control, their activities and their mutual attuning of these activities. Control elements are, for example, dispersed over the model, are not visualized, or form part of the time-indexed scheduling of events. In this article, we propose an alternative approach that explicitly addresses the modeling of control structures. First, we will conduct a literature survey with the aim of listing simulation model qualities essential for supporting successful decision making on supply chain design. Next, we use this insight to define an object-oriented modeling framework that facilitates supply chain simulation in a more realistic manner. This framework is meant to contribute to improved decision making in terms of recognizing and understanding opportunities for improved supply chain design. Finally, the use of the framework is illustrated by a case example concerning a supply chain for chilled salads.

A modeling framework for supply chain simulation: opportunities for improved decision-making

https://cyberleninka.org/article/n/662470.pdf

Literature review of deteriorating inventory models by key topics from 2012 to 2015

Production management is crucial for achieving the timely and cost-effective execution of industrial production processes. In recent years, interest has increased in the use of artificial intelligence technologies for production planning and scheduling. However, scheduling research typically has been theoretical, has had a narrow focus, and has not covered adaptation to unforeseen events. The authors' objective has been to use computer-based scheduling systems to enhance the problem-solving capabilities of human domain experts. They have developed a generic framework for building practical scheduling systems. This framework fosters the reuse of algorithms and the integration of knowledge-based technology into the organizational environment. It also supports dynamic adaptation. The authors have used it to implement scheduling systems for dye production, pipeline-fittings production and heart surgery.

Knowledge-based scheduling systems in industry and medicine

Development and simulation analysis of a new perishable inventory model with a closing days constraint under non-stationary stochastic demand

Multi-site scheduling with fuzzy concepts

In this paper, we propose a micro-periodic inventory replenishment policy for quickly perishable goods with fixed and known lifetime of items, deterministic lead time, fixed given order cycle, mixed issuing policies (FIFO and LIFO), age-based stock, imperfect items and target customer service level under random demand The inventory policy is based on time of day (morning, midday, afternoon or evening) The results of our simulation study show that the proposed micro-periodic inventory policy leads to waste reduction of 66% as well as a partial decrease in cost compared to inventory policy with planning on a daily basis

Jürgen Sauer

Papers

Literature review of deteriorating inventory models by key topics from 2012 to 2015

Knowledge-based scheduling systems in industry and medicine

Development and simulation analysis of a new perishable inventory model with a closing days constraint under non-stationary stochastic demand

Multi-site scheduling with fuzzy concepts

A stochastic micro-periodic age-based inventory replenishment policy for perishable goods