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Control of operational production systems requires a reaction to disturbances. In this paper, the authors present a Petri net model describing a decision-making mechanism induced by the breakdown of a machine. The aim of such a proposal is to reassign the operations to the workshop's resources. A decision-making aid methodology is essential to consider the disturbances according to several criteria. Therefore, the authors propose a Petri net model composed of Deterministic and Stochastic Petri nets (DSPN) and Object Petri nets (OPN). The decision-making process is based on the introduced concept of 'potential' associated with each machine. This potential is evaluated by means of several criteria to take the 'right' decision. In this study, the three following criteria are retained: Time, Cost, and machine reliability. A state of the art survey about the multicriteria decision aid methods has led to the choice of a method called AHP (Analytic Hierarchy Process). The authors thus present a multicriteria algorithm, based on the AHP method, developed for the reassignment of the operations that are blocked following a machine breakdown. The reassignment of the blocked operation is carried out on the machine providing 'the best' compromise between the three criteria.

Purpose -The impact of transportation on the supplier selection has received very scant attention in the literature. This is a great limitation because splitting orders across multiple suppliers will lead to smaller transportation quantities which will likely imply larger transportation cost. Moreover, transportation and inventory elements are highly interrelated and contribute most to the total logistics costs. This paper seeks to present a nonlinear multiobjective programming approach of selecting suppliers and allocating the order quantity among them, taking into account transportation. Design/methodology/approach -The model considers the total product cost and the lead-time as the criteria to minimize simultaneously. Findings -The total cost is the sum of transportation, inventory and ordering costs. The constraints related to suppliers and buyer are also considered in the model. The model is solved several times, evaluating various scenarios. Each scenario depends on the shipment type used between the suppliers and the buyer. Originality/value -This paper fills a gap in the literature by comprehensively examining the role of transportation in determining the optimal number of suppliers and the portion of the order to allocate to each one.