Even small improvements in storage operations can bring significant benefits in customer response time, increasing the level of service offered. However, a company cannot offer high level of service for all products. In this sense, one of the ways used to optimize the activities for order picking is the study of storage location assignment problem (SLAP). Thus, this paper proposed a multi-criteria decision model to perform the products classification and to solve the SLAP in a multi-layer warehouse. The ELECTRE TRI method is used to define the shelf level for each product, and the ELECTRE III method is used to establish a fixed location for each product on the shelf it belongs to. The great advantage of this model is that there is not trade-off among the criteria, and it is able to consider several criteria simultaneously. However, the main goal is not optimization, but the search for a storage operations performance balance, considering multiple criteria, allowing for a better inventory management when consideringprofitabilitycriteria,for example,andimprovement inthe order picking operations, through the demand and space required criteria. In addition, it considers the preferences of the decision maker.
This paper presents a Decision Support System (DSS)to project software management that uses a hybrid methodology. This is based on a combination of linear programming method, for assignment of tasks, and the task management method, Scrum. This proposal aids in management and optimization of the time of completion of the project or sprint without removing the inherent flexibility of agile methodologies. A support tool was developed to assist in the applicability of DSS. It is concluded that the DSS proposed can assign tasks to minimize the total execution time of the sprint and it assists the managers in assessing developers, since it will be possible to determine whether they are meeting the deadlines within established goals for their level of seniority.Keywords-component; decision support system, project software management, scrum metodology, level of seniority.
Goal: This study developed a structured decision model capable of solving the storage location assignment problem (SLAP) in a picker-to-parts system, using multiples key performance indicators (KPIs). Design / Methodology / Approach: A hybrid approach was developed. For that, a Multi-Objective Genetic Algorithm (MOGA) was used considering three fitness functions, but more functions may be considered. Through MOGA it was possible to verify a high number of solutions and reduce it into a Pareto frontier. After that, a Multiple-Criteria Decision-Making (MCDM) approach was used to choose the best solution. Results: This model was able to find viable solutions considering multiples objectives, warehouse restrictions and decision makers' preferences, and the required processing time for the simulated cases was insignificant. Limitations of the investigation: One limitation of this work was the consideration of known and predictable data. Practical implications: The proposed model was developed with the purpose of assisting companies that face this type of problem, providing a solution for SLAP requiring the minimum information and operational actions. Originality / Value: SLAP is a NP (Non-Deterministic Polynomial time) complex problem and, after the MOGA, the number of solution can be still high for the final decision making by the engineering manager (decision maker-DM). Thus, the MOGA-MCDM hybrid approach developed was able incorporate the DM' preferences into a compensatory view, vetoing alternatives that were worse in any of the KPIs, to recommend a final solution.
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