Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation
Computers and Industrial Engineering
Computers and Industrial Engineering
Genetic Algorithms and Fuzzy Multiobjective Optimization
Genetic Algorithms and Fuzzy Multiobjective Optimization
Fuzzy mathematical programming for multi objective linear fractional programming problem
Fuzzy Sets and Systems - Theme: Decision and optimization
Production-distribution planning in supply chain considering capacity constraints
Computers and Industrial Engineering - Supply chain management
Multicriterion genetic optimization for due date assigned distribution network problems
Decision Support Systems - Special issue: Collaborative work and knowledge management
Multicriterion genetic optimization for due date assigned distribution network problems
Decision Support Systems - Special issue: Collaborative work and knowledge management
Multi-criteria logistics distribution network design using SAS/OR
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
International Journal of Knowledge-based and Intelligent Engineering Systems
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This paper focuses on the demand due date factor in multiechelon distribution network problems and its impact on the production scheduling in manufacturing plants. A reliable demand due date is critical in winning of customer orders. However, this may usually require high collaboration among entities in the network. Mismatching of one single schedule may seriously influence the reliability. In this connection, holistically optimizing the schedule of each entity among the network is essential. In addition, on time delivery may induce high operating cost. A trade-off between earliness, on time, and tardiness should also be considered. Hence, a multicriterion genetic optimization methodology is developed to holistically optimize them. It determines the optimized schedule to collaborate each entity to fulfill the demands. For enabling multicriterion decision-making, the proposed algorithm combines analytic hierarchy process with genetic algorithms (GAs). The problem is divided into two parts-(i) demand allocation and transportation problem, and (ii) production scheduling problem. The optimization approach is applied to iteratively optimize part (i), and then part (ii). Three experiments have been carried out, and the computation results show that the effect of due date is critical, and the ability of the proposed algorithms in taking trade-off between earliness and tardiness.