In this work, we analyse the chicken production in a poultry network composed of a set of farms that serves a slaughterhouse in the city of Tlemcen. Each farm has a chicken house dedicated to breeding, and each chicken house has three breeding modes: manual breeding, semi-automatic breeding, and automatic breeding. And each mode consumes an appropriate energy level depending on the degree of automation used, which directly affects the quality of the chicken. The objective of this study is to determine the best energy adaptation within the farm to obtain good quality chickens. The problem of this activity is the choice of the right energy level of breeding, which consumes a minimum energy value, and gives a good quality of chickens. Knowing that the quality improves with the increase of energy, this study serves to develop mathematical modelling of two objectives: minimization of energy consumption and maximization of the chicken quality produced. The two objectives are optimized independently, and then they are joined by adapting the LP-metric method to help the breeders choose the optimal energy level to obtain good quality chickens.
In this paper we analyze a distribution network and a waste collection network that adopt the same fleet of vehicles. This fleet is owned by a company that provides logistics and transport services in the Algerian territory. The objective of this work is to propose a logistics chain in circular economy (continuous cycle) by combining the transports of the two studied networks, taking advantage of the empty returns, in order to minimize the travel costs and to reduce the CO2 emissions. The purpose of this study is to investigate the impact of optimal vehicle usage in distribution networks and its influence on total supply chain costs and environmental effects.
In this work, we study a multi-objective problem in a pharmaceutical production unit composed of several production stations that produce several kinds of products. The goal of this work, in a first step, is to propose a scheduling at the production unit in order to establish a synchronization of the different tasks on the m-machines. The problem can be formulated by the scheduling of a multi-product flow-shop.Then, we take into account the energy constraints of each task to be done. The problem can be formulated by a linear multi-objective MILP program, where the first objective is to determine the best sequence that minimizes the production and launch costs. In addition, the second objective is to find the best sequence that minimizes energy consumption. The problem is formulated and solved by combining the NEH heuristic and the LP-metric method to determine an intermediate solution between minimizing production costs and minimizing energy consumption.
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