A possibilistic approach to the modeling and resolution of uncertain closed-loop logistics

Abstract

Closed-loop logistics planning is an important tactic for the achievement of sustainable development. However, the correlation among the demand, recovery, and landfilling makes the estimation of their rates uncertain and difficult. Although the fuzzy numbers can present such kinds of overlapping phenomena, the conventional method of defuzzification using level-cut methods could result in the loss of information. To retain complete information, the possibilistic approach is adopted to obtain the possibilistic mean and mean square imprecision index (MSII) of the shortage and surplus for uncertain factors. By applying the possibilistic approach, a multi-objective, closed-loop logistics model considering shortage and surplus is formulated. The two objectives are to reduce both the total cost and the root MSII. Then, a non-dominated solution can be obtained to support decisions with lower perturbation and cost. Also, the information on prediction interval can be obtained from the possibilistic mean and root MSII to support the decisions in the uncertain environment. This problem is non-deterministic polynomial-time hard, so a new algorithm based on the spanning tree-based genetic algorithm has been developed. Numerical experiments have shown that the proposed algorithm can yield comparatively efficient and accurate results.

A Systematic Literature Review of MABAC Method and Applications: An Outlook for Sustainability and Circularity

“…Plenty of researchers have counted on and utilized the MADM and MODM models as formal and standard methodologies using the obtainable technical information to balance and assess stakeholder values, develop solutions and enhance environmental and social sustainability. One of the most-addressed fields is Supply Chain Management (SCM) (Haleh and Hamidi, 2011;Wang and Hsu, 2012).…”

Multistage production distribution under uncertain demands with integrated discrete particle swarm optimization and extended priority-based hybrid genetic algorithm

“…Wang and Hsu (2012) applied the possibilistic mean and mean square imprecision index of the shortage and surplus for uncertain factors in the closed-loop logistics model. Zeballos et al (2014) proposed mixed-integer linear programming for 10 layers (five stages) of closed-loop supply chains with uncertain supply and demand.…”