Probabilistic Programming with Piecewise Objective Function for Solving Supplier Selection Problem with Price Discount and Probabilistic Demand

In this article, a supplier selection problem with price discount and probabilistic demand was solved by formulating a new probabilistic programming model with a piecewise objective function. The proposed model was able to be used by the decision-maker to calculate the optimal decision involving the appropriate raw material quantity to be ordered from each supplier to have minimal total procurement cost. A numerical experiment was conducted with some randomly generated data and the results showed the supplier selection problem was solved by the proposed model and the optimal decision value is achieved

Integration of Ergonomic Aspects into Lot-sizing Model of the Production Line Supply Process Based on Relaxation Allowance and Maximum Endurance Time

The maximum endurance time is a key parameter for the estimation of relaxation allowance and rest time. Recently, researchers have started to investigate and integrate particularly economic aspects of sustainability as well as environmental sustainability dimensions in intralogistics systems, and only a few contributions studied the social aspect of sustainability. Therefore, the aim of the paper is the extension and development of a new cost model based on relaxation allowance and endurance time. The effects of endurance time and relaxation allowance on the total cost of logistics operation were investigated. The developed new model considered the maximum endurance time for calculation of rest time necessary for different quantities of handled items and item weights. The results of comparison with the total cost of maximum lifting and carrying (25 kg) limit for two-handed lifting show that the percentage savings achieved with the implementation of our new model from using ergonomic rest time and maximum endurance time was equal to 43.2% in the total cost of production line supply process