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

Market-based Recommendation: Agents that Compete for Consumer Attention

The amount of attention space available for recommending suppliers to consumers on e-commerce sites is typically limited. We present a competitive distributed recommendation mechanism based on adaptive software agents for efficiently allocating the 'consumer attention space', or banners. In the example of an electronic shopping mall, the task is delegated to the individual shops, each of which evaluates the information that is available about the consumer and his or her interests (e.g. keywords, product queries, and available parts of a profile). Shops make a monetary bid in an auction where a limited amount of 'consumer attention space' for the arriving consumer is sold. Each shop is represented by a software agent that bids for each consumer. This allows shops to rapidly adapt their bidding strategy to focus on consumers interested in their offerings. For various basic and simple models for on-line consumers, shops, and profiles, we demonstrate the feasibility of our system by evolutionary simulations as in the field of agent-based computational economics (ACE). We also develop adaptive software agents that learn bidding strategies, based on neural networks and strategy exploration heuristics. Furthermore, we address the commercial and technological advantages of this distributed market-based approach. The mechanism we describe is not limited to the example of the electronic shopping mall, but can easily be extended to other domains

Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms

The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of theoptimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty

The need for inventory control models for practical real-world applications is growing with the global expansion of supply chains. The widely used traditional optimization procedures usually require an explicit mathematical model formulated based on some assumptions. The validity of such models and approaches for real world applications depend greatly upon whether the assumptions made match closely with the reality. The use of meta-heuristics, as opposed to a traditional method, does not require such assumptions and has allowed more realistic modeling of the inventory control system and its solution. In this dissertation, a metaheuristic-based simulation optimization framework is developed for supply chain inventory management under uncertainty. In the proposed framework, any effective metaheuristic can be employed to serve as the optimizer to intelligently search the solution space, using an appropriate simulation inventory model as the evaluation module. To be realistic and practical, the proposed framework supports inventory decision-making under supply-side and demand-side uncertainty in a supply chain. The supply-side uncertainty specifically considered includes quality imperfection. As far as demand-side uncertainty is concerned, the new framework does not make any assumption on demand distribution and can process any demand time series. This salient feature enables users to have the flexibility to evaluate data of practical relevance. In addition, other realistic factors, such as capacity constraints, limited shelf life of products and type-compatible substitutions are also considered and studied by the new framework. The proposed framework has been applied to single-vendor multi-buyer supply chains with the single vendor facing the direct impact of quality deviation and capacity constraint from its supplier and the buyers facing demand uncertainty. In addition, it has been extended to the supply chain inventory management of highly perishable products. Blood products with limited shelf life and ABO compatibility have been examined in detail. It is expected that the proposed framework can be easily adapted to different supply chain systems, including healthcare organizations. Computational results have shown that the proposed framework can effectively assess the impacts of different realistic factors on the performance of a supply chain from different angles, and to determine the optimal inventory policies accordingly

Determine planning method in the storage area

ABSTRACT Ji Yuan Hai Wan Shi Ye AB started in the December of 2011, is co-funded by the Xiamen Hai Wan AB and Luo Yang Shi Hua. It has integrated business such as scientific research, production and trade together. The company locates in the industrial manufactory area at Ji Yuan, Henan Province. The main products are verity of unsaturated polyester resin. Their products are widely used in the fields like industry, agricultural, transportation and construction. This shows its wide coverage status quo and broad future (Company´s website). Inventory is the network-node among goods flow, information flow and cash flow, and is of great importance to economic development nowadays. The rational management in transportation, packaging, loading/unloading, processing, delivery, can efficiently alleviate working strength, damage ratio, Inventory turnover and distribution costs. The storage area is not only the most important but also the most difficult part to plan. According to the statistics, unloading, picking, sorting and loading take 40% time of the whole process, and the rest are consumed by staff’s patrolling. As a result, a cost effective design in storage area can effectively lower down internal transportation cost, and highly improve the performance of the whole inventory. In order to increase the efficiency inside storage area, and create a best possible environment for material handlers in the inventory; this article intended to generate a directive description by studying the design inside storage area of the inventory. Based on the case study, author has raised a recommendation to the inventory´s equipment and slot planning. MATLAB is the main programming tool in the slot planning and it contains aspects below: 1, A brief introduction to company and their main activities. 2, Storage area planning and design theories: The definition, types, functions of storage area were introduced in the beginning. Then storage area and several ways of storage were briefly described. At last, author described the classical EIQ analysis and its applications in the logistics system. Page IV 3, Selection of equipment in storage area Author elaborated basic principles of the equipment choice; and introduced types, choice methods in storing and material handling equipment. Finally the EIQ analysis was applied and its influence in equipment choice was proved. 4, Planning and design of slots in the storage area This part mainly included following contents A. Coding The article began with methodology introduction for the coding of both location and goods, and the principles of choice methodology for different goods. B. Spacing plan and corresponding information Principles and concepts of location planning as well as corresponding benefits were introduced, which are the reasons of location planning. C. Modeling The author has presented the aim of the location planning; and according to that, a model has been introduced. There are two things has to be concerned, one is the total transporting distance for the goods and the other one is the stability of the racking. The aim of the location planning is to increase picking efficiency by storing the fastest-moving goods in the most convenient positions which is gate in this case. To increase racking ´s stability, lighter goods have to put in higher than heavier things. D. The algorithm Location planning is a multi-objective optimization problem. Author has analyzed and compared several algorithms; finally genetic algorithm was chosen to solve the problem. Author introduced the principles of the methodology about using genetic algorithm to solve a multi-objective optimization problem. After that, according to the model introduced in the previously step, author has decided to use parallel selection method, multi-Gender evolutionary method and constraint method. To get an optimal solution of location planning, MATLAB has been used as the tool. Page V 5, Applied and analyzed the methods and programs, mentioned in the article, to the design of inventory´s storage area. 6, Summary and prospect Author has summarized the article’s result and raised future research topics. This article has given some new points in the following aspect： 1．By thinking of velocity of goods circulation and goods weigh, a multi-objective optimization model for location planning has been made. Model has been solved, via using Genetic Algorithm’s paratactic selection, multi-gender evolution and constraint methods. 2．By using MATLAB, author programmed the location plan which generates solutions to optimization problems using techniques inspired by natural evolution. Programming has been used crossover, mutation methods and the algorithm terminated when the 500 generations has been produced, then a satisfactory fitness solution has been reached for the location

Integrated Production and Distribution planning of perishable goods

Tese de doutoramento. Programa Doutoral em Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 201