Abstract. This study is concerned with how the quality of perishable products can be improved by shortening the time interval between production and distribution. Since special types of food, such as dairy products, decay fast, the Integration of Production and Distribution Scheduling (IPDS), is investigated. This article deals with a variation of IPDS that contains a short shelf life product; hence, there is no inventory of the product in the process. Once a speci c amount of the product is produced, it must be transported with the least transportation time directly to various customer positions within its limited lifespans to minimize the delivery and tardy costs required to complete producing and distributing of the product to satisfy the demand of customers within the limited deadline. After developing a mixed-integer nonlinear programming model of the problem, because it is NP-hard, an Improved Particle Swarm Optimization (IPSO) is proposed. IPSO performance is compared with commercial optimization software for small-size and moderate-size problems. For large-size ones, it is compared with the genetic algorithm existing in the literature. Computational experiments show the e ciency and e ectiveness of the proposed IPSO in terms of both the quality of the solution and the time of achieving the best solution.
This paper introduces a multi-factory scheduling with batch delivery problem. A novel mixed-integer programming model is proposed to minimize the sum of total tardiness, holding and batching costs. A bi-level decomposition algorithm (BLDA) is developed involving two sub-problems: scheduling problem in the upper level and batching problem in the lower level. Four versions of the BLDA are created by combinations of CPLEX and simulated annealing in both levels, which interactively collaborate until the algorithm converges to a solution. The BLDAs are examined on several random and real-life test instances. A statistical analysis is performed by comparing the BLDAs’ solutions with the exact minimum and lower bound values of the total cost. The results indicate that about all versions of the developed BLDA provide high quality solutions for real-world zinc industry problems as well as generated instances in a reasonably short time. Finally, some managerial insights are derived based on sensitivity analysis.
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