Strategic Planing
Sajad Moradi
Abstract
Purpose: This article studies an issue in the fish farming industry in which the goal is to find the best multi-period planning for handling various chains, including ordering, breeding, and selling of trout over a time horizon.Methodology: In this study, a new formulation is presented as a mixed integer ...
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Purpose: This article studies an issue in the fish farming industry in which the goal is to find the best multi-period planning for handling various chains, including ordering, breeding, and selling of trout over a time horizon.Methodology: In this study, a new formulation is presented as a mixed integer linear programming model that could find the optimum solution quickly. In the new proposed formulation, some intermediate stages of the breeding chain that do not affect decisions are ignored, and therefore, the size and complexity of the proposed model reduce without compromising the optimality of the answers.Findings: After implementing the proposed model, using different data samples, it can be seen that this model achieves the optimal solution in a short time, including volume and time of spawning in each breeding chain and different periods, harvesting time, and accepting or rejecting the main demands.Originality/Value: In this paper, the issue of scheduling of fish farming chains and sales management, which there are a few studies in this field, has been studied and a new mixed integer linear programming model is presented. Compared to the previous model, this model has more realistic assumptions and less complexity and execution time.
Linear Optimization
Sajad Moradi; Gholamreza Karamali
Abstract
Shortest path problem is one of the practical issues in optimization, and there are many efficient algorithms in this area. In this issue, a network of some nodes and arcs is considered in which, each arc has a specific parameter such as distance or cost. The main objective is to find the shortest or ...
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Shortest path problem is one of the practical issues in optimization, and there are many efficient algorithms in this area. In this issue, a network of some nodes and arcs is considered in which, each arc has a specific parameter such as distance or cost. The main objective is to find the shortest or least costly route between two distinct points. By considering an additional parameter and adding a new limitation, as a capacity constraint, the problem will be closer to the real world condition. This extended issue is known as the constrained shortest path problem and has a higher complexity order and practical algorithms are needed to solve it. In this study, an effective algorithm is presented that obtains the optimal solution within a short time. In this method, a repetitive pattern is used so that, in each iteration, the relaxed model, after adding a logical cut, is solved. The results of the implementation of the proposed algorithm on different networks show its efficiency.