AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Perbandingan Teknik Pengkodean Langsung dan Tidak Langsung pada Kasus Penjadwalan Jobshop

Development of technology help human life in problem solving. Scheduling is a one of the problem which could be solved with it. In scheduling research, jobshop case is frequently used to test the scheduling problem solving algorithm. This study provide the comparison between direct encoding and indirect encoding approach. These approach are choices in jobshop secheduling problem research. The apparent differences of these approach are in used technique. Genetic algorithm is used as the testing algorithm. The Cases which will be used are the common cases from OR-Lib. The testing is done by looking the makespan, processing time, and objective value transformation. Testing result shows the direct encoding approach found more small makespan. Whereas indirect encoding approach can found optimal makespan in running with large number of generation

THE IMPROVED SWEEP METAHEURISTIC FOR SIMULATION OPTIMIZATION AND APPLICATION TO JOB SHOP SCHEDULING

We present an improved sweep metaheuristic for discrete event simulation optimization. The sweep algorithm is a tree search similar to beam search. The basic idea is to run a limited number of partial solutions in parallel and to search for solutions by searching the partial solutions. Traditionally, simulation optimization is carried out by multiple simulation runs executed sequentially. In contrast, the sweep algorithm executes multiple simulation runs simultaneously. It uses branching and pruning simulation models to carry out optimization. We describe new components of the algorithm, such as backtracking and local search. Then, we compare our approach with 13 metaheuristics in solving job shop scheduling benchmarks. Our approach ranks in the middle of the comparison which we regard as a success. The general nature of tree search offers a large array of sequential decision applications for the sweep algorithm, such as resource-constrained project scheduling, traveling salesman, or (real-time) production scheduling.

The Study of Solving the Problem Having Multiple Search Spaces by Hierarchical Optimize Method Based on the Competitive

九州工業大学博士学位論文 学位記番号:生工博甲第266号 学位授与年月日:平成28年3月25日第1章 序論|第2章 問題設定と関連手法|第3章 複数解空間競合型分散GAの提案と多項式曲線フィッティングによる検証|第4章 階層的複数解空間競合型分散GAの提案と階層的な組み合わせ最適化問題への適用|第5章 結論九州工業大学平成27年

Lot Streaming in Different Types of Production Processes: A PRISMA Systematic Review

At present, any industry that wanted to be considered a vanguard must be willing to improve itself, developing innovative techniques to generate a competitive advantage against its direct competitors. Hence, many methods are employed to optimize production processes, such as Lot Streaming, which consists of partitioning the productive lots into overlapping small batches to reduce the overall operating times known as Makespan, reducing the delivery time to the final customer. This work proposes carrying out a systematic review following the PRISMA methodology to the existing literature in indexed databases that demonstrates the application of Lot Streaming in the different production systems, giving the scientific community a strong consultation tool, useful to validate the different important elements in the definition of the Makespan reduction objectives and their applicability in the industry. Two hundred papers were identified on the subject of this study. After applying a group of eligibility criteria, 63 articles were analyzed, concluding that Lot Streaming can be applied in different types of industrial processes, always keeping the main objective of reducing Makespan, becoming an excellent improvement tool, thanks to the use of different optimization algorithms, attached to the reality of each industry.This work was supported by the Universidad Tecnica de Ambato (UTA) and their Research and Development Department (DIDE) under project CONIN-P-256-2019, and SENESCYT by grants “Convocatoria Abierta 2011” and “Convocatoria Abierta 2013”