To save overhead and penalty costs, in many cases of Multi-Period Multi-Product (MPMP) planning systems, reducing the completion time is highly desirable. Therefore, in this paper we study this problem. We propose an approach in which a MPMP problem is converted into a project management network. Then, considering network concepts and properties, a multi stage novel mathematical model is propos...

Generally, the inventory routing problem occurs in a supply chain where customers consider the supplier responsible for inventory replenishment. In this situation, the supplier finds the answer to questions regarding the time and quantity of delivery to the customer as well as the sequence of customers in the routes. Considering the effect of production decisions on answering these questions, t...

We consider production planning problems with uncertainties in the problem data. The optimization problems are formulated as two-stage stochastic mixed-integer models in which some of the decisions (first-stage) have to be made under uncertainty and the remaining decisions (second-stage) can be made after the realization of the uncertain parameters. The uncertain model parameters are represente...

Following the occurrence of unexpected events and natural disasters, a highly important relief operation is the transferring of relief commodities from the distribution centers (CDs) to shelters. In this paper, a three-level network consisting of depot of vehicles, distribution centers and shelters has been considered for routing and scheduling of relief vehicles through introducing a multi-obj...

In this paper, the ability of Immune Algorithm (IA) is investigated for VAr planning with the Static Var Compensator (SVC) in a large-scale power system. To enhance voltage stability, the planning problem is formulated as a multi-objective optimization problem for maximizing fuzzy performance indices. The multi-objective VAr planning problem is solved by the fuzzy IA and the results are compare...

Nowadays, there has been a growing interest in recovery options such as recycling, remanufacturing and reusing in the scope of Reverse Logistics (RL) and Closed-Loop Supply Chain (CLSC) concepts due to the environmental, economical issues and legal obligations. Due to this fact, companies should take into account the utilized recovery option while preparing both strategic planning and tactical ...

In industries machine maintenance is used in order to avoid untimely machine fails as well as to improve production effectiveness. This research regards a permutation flow shop scheduling problem with aging and learning effects considering maintenance process. In this study, it is assumed that each machine may be subject to at most one maintenance activity during the planning horizon. The objec...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...

scheduling for job shop is very important in both fields of production management and combinatorial op-timization. however, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. the combination of several optimization criteria induces additional complexity and new problems. in this paper, we pro...

nowadays, the necessity of accurate quantitative decision support methods is becoming a critical subject for managers as rivalry between organizations caused a more fragile economic environment and brand reputation is becoming more important. furthermore, dealing with incidents after they happened is not accepted by customers anymore. managers require powerful decision making tools to support t...