This paper proposes a new mixed integer programming model for multi-item capacitated lot-sizing problem with setup times, safety stock and demand shortages in closed-loop supply chains. The returned products from customers can either be disposed or be remanufactured to be sold as new ones again. Due to the complexity of problem, three meta-heuristics algorithms named simulated annealing (SA) al...

This paper proposes a mixed integer programming model for single-item capacitated lot-sizing problem with setup times, safety stock, demand shortages, outsourcing and inventory capacity. Due to the complexity of problem, three meta-heuristics algorithms named simulated annealing (SA), vibration damping optimization (VDO) and harmony search (HS) have been used to solve this model. Additionally, ...

Some recent trends in manufacturing in particular and business in general, lead to new approaches regarding the organisation and software architecture, mainly adopting distributed solutions. Such organisations imply organisational and technological evolution through agility, distribution, decentralisation, reactivity and flexibility. New organisational and technological paradigms are needed in ...

Many real-world optimization problems today are multi-objective multi-constraint generalizations of NP-hard problems. A classic case we study in this paper is the Inventory Routing Problem with Time Windows (IRPTW). IRPTW considers inventory costs across multiple instances of Vehicle Routing Problem with Time Windows (VRPTW). The latter is in turn extended with time-windows constraints from the...

in this paper a non linear integrated fuzzy multi-objective production planning model with the labor learning and machines deterioration effects is presented. the objective function consists of two quantitative objectives namely increase profits and reduces the cost of system failure and a qualitative objective namely increases the satisfaction rate of the customers. different weights for objec...

Combinatorial optimization problems are often used to test heuris-tics. Among heuristics, stochastic ones deserve particular consideration being generally meta-heuristics that aim at performing reasonnably well on a wide spectrum of problems. Among them, evolutionary algorithms have recently appeared. Emphasis have been put on them by researches that have shown that they are able to solve eecie...

Parameter tuning is recognized today as a crucial ingredient when tackling an optimization problem. Several meta-optimization methods have been proposed to find the best parameter set for a given optimization algorithm and (set of) problem instances. When the objective of the optimization is some scalar quality of the solution given by the target algorithm, this quality is also used as the basi...

Extensive research has been devoted to economic production quantity (EPQ) problem. However, little atten-tion has been paid to problems where depreciation cost and process quality cost must be considered, simulta-neously. In this paper, we consider the economic production quantity model of minimizing the annual total cost subject to depreciation cost and process quality cost, where depreciation...

extensive research has been devoted to economic production quantity (epq) problem. however, little atten-tion has been paid to problems where depreciation cost and process quality cost must be considered, simulta-neously. in this paper, we consider the economic production quantity model of minimizing the annual total cost subject to depreciation cost and process quality cost, where depreciation...

Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...