Outsourcing is a good strategy for firms that need to reduce operating costs and improve competitiveness, but it remains important for firms to scientifically select the appropriate outsourcing providers. Some efforts have been made regarding outsourcing problems, but these efforts incorrectly assumed that the criteria in the decision process are independent, which is not true in the real world...

Abstract: Bi-level programming, a tool for modeling decentralized decisions, consists of the objective(s) of the leader at its first level and that is of the follower at the second level. Three level programming results when second level is itself a bi-level programming. By extending this idea it is possible to define multi-level programs with any number of levels. Supply chain planning problem...

in traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. so decision maker cannot estimate them exactly. financial optimization is one of the most attractive areas in decision under uncertainty. in the portfolio selection problem the decision maker considers simultaneously conflicting objectives such as ra...

Microgrid implementation often lacks economic and environmental efficiencies due to sub-optimal configuration operation. The current study aims explore the optimal operational strategies for a microgrid system with maximum life cycle co-benefits. This was inspired by real optimization need Shoals Marine Laboratory, seasonal marine teaching research field station on Appledore Island, Maine. A dy...

We propose a Mamdani-Type Fuzzy Inference based posterior decision-making approach to multi-objective diet optimization problem. optimize the problem with evolutionary algorithms that result in tens/hundreds of non-dominated solutions which is too large pick one them by decision-maker. Even though all are optimized for objectives simultaneously, not objective functions may be equally important ...

Abstract In many real-world scenarios, the utility of a user is derived from single execution policy. this case, to apply multi-objective reinforcement learning, expected returns must be optimised. Various scenarios exist where user’s preferences over objectives (also known as function) are unknown or difficult specify. such set optimal policies learned. However, settings maximised have been la...