Design of a Hybrid Genetic Algorithm for Parallel Machines Scheduling to Minimize Job Tardiness and Machine Deteriorating Costs with Deteriorating Jobs in a Batched Delivery System

This paper studies the parallel machine scheduling problem subject to machine and job deterioration in a batched delivery system. By the machine deterioration effect, we mean that each machine deteriorates over time, at a different rate. Moreover, job processing times are increasing functions of their starting times and follow a simple linear deterioration. The objective functions are minimizing total tardiness, delivery, holding and machine deteriorating costs. The problem of total tardiness on identical parallel machines is NP-hard, thus the under investigation problem, which is more complicated, is NP-hard too. In this study, a mixed-integer programming (MILP) model is presented and an efficient hybrid genetic algorithm (HGA) is proposed to solve the concerned problem. A new crossover and mutation operator and a heuristic algorithm have also been proposed depending on the type of problem. In order to evaluate the performance of the proposed model and solution procedure, a set of small to large test problems are generated and results are discussed. The related results show the effectiveness of the proposed model and GA for test problems

Multiobjective Robust Possibilistic Programming Approach to Sustainable Bioethanol Supply Chain Design under Multiple Uncertainties

In this article, a multiobjective mixed-integer linear programming (MILP) model is proposed to address the optimal design and planning of a lignocellulosic bioethanol supply chain (LBSC) considering a sustainable supply chain optimization framework including economic, environmental, and social objectives. The proposed model is capable of determining strategic decisions, including biomass sourcing and allocation, locations, capacity levels, and technology types of biorefinery facilities, as well as the tactical decisions, including inventory levels, production amounts, and shipments among the network. Eco-indicator 99, which is a well-known life-cycle-assessment- (LCA-) based environmental impact assessment method, is incorporated into the model to estimate the relevant environmental impacts. To handle the inherent uncertainty of the input data in the problem of interest, a novel multiobjective robust possibilistic programming (MORPP) approach is developed. The performance of the model is demonstrated through a case study developed for a biofuel supply chain in Iran. Diverse solutions achieved by the proposed MORPP approach outperform deterministic solutions in terms of given performance measures