Multi-agent supply chain scheduling problem by considering resource allocation and transportation

Today in the global market competition, integration issue in supply chain is considered as an important principle. In this study, for the first time, different requirements of the customers and different aims of the manufacturer are simultaneously addressed in an integrated problem of production scheduling, transportation, and resource allocation. The problem consists of two types of customers, considered as the agents. The first agent accepts tardiness in delivery of orders provided that the manufacturer pays the tardiness penalty; whereas, the second agent does not accept the tardy orders. The purpose is to minimize the sum of batch delivery cost, resource allocation, tardiness penalty cost, and lost sale cost (the total number of tardy orders). To solve the problem, two mathematical programming models, including a Mixed Integer Non-Linear Programming (MINLP) and a Mixed Integer Linear Programming (MILP) are proposed. Also, due to NP-hard nature of the problem, two meta-heuristic algorithms of Adaptive Genetic Algorithm (AGA) and Ant Lion Optimization (ALO), as well as a heuristic algorithm are proposed. To assess the merits of the solution methods, small and large-scale tests are designed. The results indicate the superiority of adaptive genetic algorithm in comparison with other algorithms.