One of the important aspects of distribution optimization problems is simultaneously, controlling the inventory while devising the best vehicle routing, which is a famous problem, called inventory-routing problem (IRP). When the lot-sizing decisions are jointed with IRP, the problem will get more complicated called production inventory-routing problem (PIRP). To become closer to the real life p...

In agricultural economics, several calibration and aggregation approaches have evolved in mathematical programming models. This article combines in a linear programming model features of the Positive Mathematical Programming method with an aggregation approach that is constrained to the production possibility set spanned by a convex combination of observed production activities. The combination...

recently, lotfi et al. [10] established an equivalence model between the output-oriented dual ccr model and multiple objective linear programming (molp) and used an interactive method for finding target unit on efficiency frontier such that the decision maker preferences can be taken into account. however their method is not applicable for situations in which some outputs are undesirable and ne...

This contribution describes a general mixed-integer linear programming model based on a time-indexed formulation covering the relevant features required for the complete supply chain management of a multi-site production network. While the actual application is taken from the chemical industry, the model provides a starting point for many applications in the chemical process industry, food or c...

This paper presented an application of Fuzzy mathematical programming model to solve network design problems for supply chains via considering aggregate production planning (APP). APP goals to minimize all costs through optimal levels of production, subcontracting, inventory, backorder and work levels over a time period to meet the demand. Fuzzy logic was applied to solve the uncertain producti...

Management of French electricity production to control cost while satisfying demand, leads to solve a stochastic optimization problem where the main sources of uncertainty are the demand load, the electricity and fuel market prices, the hydraulicity, and the availability of the thermal production assets. A stochastic dynamic programming method is an interesting solution, but is both CPU and mem...