Combining Fix and Relax Heuristic and LP-Metric Method to Solve the Multi-Objective Integrated Production-Routing Problem

Production routing problem is one of the problems of the integrated planning that interests in optimizing simultaneously production, inventory, and distribution planning. This chapter has the purpose of developing two mono-objective models for the production-routing problem: one of them minimizes the total costs which is the classical objective while the other one minimizes the energy consumed by the production system. A bi-objective model is then proposed to combine the two objectives mentioned previously using LP-metric method. To solve big instances of the problem in reasonable time, an approximate approach is proposed using the rolling horizon-based fix and relax heuristic. Finally, computational results are presented to compare the solutions obtained by both approaches.

A mathematical model for production routing of mechanical engineering products

The aim was to create a mathematical model describing the development of a production (shop-to-shop) routing of mechanical engineering products based on a 3D model and allowing the cost of the final product to be reduced. The developed mathematical model was simulated based on 3D models designed in the Siemens NX system, which were subsequently imported into the *stp format and recognized by a designed module written in the Phyton programming language. The factors of the production environment affecting the formation of the production routing of mechanical engineering products were determined. A diagram of the algorithm for the “constructive element - technological operation - means of technological equipment (equipment-tool)” relationship was developed. Based on the results of testing the developed mathematical model, the use of neural networks as a tool for the implementation and automation of the work was found advantageous as compared to the standard scheme of work of a process engineer when developing a production routing of mechanical engineering products. These advantages include a decrease in the time for the development of a routing and the cost of the final product. The developed model has a practical limitation consisting in a rather complex geometry of some structural elements of a unit, which impedes the development of an algorithm for recognizing their structure. The use of a neural network prototype in automatic mode is advisable for relatively simple parts (including a flange, hole, chamfer and rounding). However, since the number of simple units from the recognition point of view amounts to about 40% among the nomenclature of manufactured units, the reduction in the development time of the technological process in comparison with the conventional approach comprises only 10–25% of the total time of technological preparation.

A robust possibilistic programming model for production-routing problem in a three-echelon supply chain

Purpose This paper aims to provide an integrated production-routing model in a three-echelon supply chain containing a two-layer transportation system to minimize the total costs of production, transportation, inventory holding and expired drugs treatment. In the proposed problem, some specifications such as multisite manufacturing, simultaneous pickup and delivery and uncertainty in parameters are considered. Design/methodology/approach At first, a mathematical model has been proposed for the problem. Then, one possibilistic model and one robust possibilistic model equivalent to the initial model are provided regarding the uncertain nature of the model parameters and the inaccessibility of their probability function. Finally, the performance of the proposed model is evaluated using the real data collected from a pharmaceutical production center in Iran. The results reveal the proper performance of the proposed models. Findings The results obtained from applying the proposed model to a real-life production center indicated that the number of expired drugs has decreased because of using this model, also the costs of the system were reduced owing to integrating simultaneous drug pickup and delivery operations. Moreover, regarding the results of simulations, the robust possibilistic model had the best performance among the proposed models. Originality/value This research considers a two-layer vehicle routing in a production-routing problem with inventory planning. Moreover, multisite manufacturing, simultaneous pickup of the expired drugs and delivery of the drugs to the distribution centers are considered. Providing a robust possibilistic model for tackling the uncertainty in demand, costs, production capacity and drug expiration costs is considered as another remarkable feature of the proposed model.

A Memetic Algorithm for an External Depot Production Routing Problem

This study aims to compare the results of a memetic algorithm with those of the two-phase decomposition heuristic on the external depot production routing problem in a supply chain. We have modified the classical scheme of a genetic algorithm by replacing the mutation operator by three local search algorithms. The first local search consists in exchanging two customers visited the same day. The second consists in trying an exchange between two customers visited at consecutive periods and the third consists in removing a customer from his current tour for a better insertion in any tour of the same period. The tests that were carried out on 128 instances of the literature have highlighted the effectiveness of the memetic algorithm developed in this work compared to the two-phase decomposition heuristic. This is reflected by the fact that the results obtained by the memetic algorithm lead to a reduction in the overall average cost of production, inventory, and transport, ranging from 3.65% to 16.73% with an overall rate of 11.07% with regard to the results obtained with the two-phase decomposition heuristic. The outcomes will be beneficial to researchers and supply chain managers in the choice and development of heuristics and metaheuristics for the resolution of production routing problem.