  In this letter, we study the resource allocation for a multiuser intelligent
reflecting surface (IRS)-aided simultaneous wireless information and power
transfer (SWIPT) system. Specifically, a multi-antenna base station (BS)
transmits energy and information signals simultaneously to multiple energy
harvesting receivers (EHRs) and information decoding receivers (IDRs) assisted
by an IRS. Under this setup, we introduce a multi-objective optimization (MOOP)
framework to investigate the fundamental trade-off between the data sum-rate
maximization and the total harvested energy maximization, by jointly optimizing
the energy/information beamforming vectors at the BS and the phase shifts at
the IRS. This MOOP problem is first converted to a single-objective
optimization problem (SOOP) via the $\epsilon$-constraint method and then
solved by majorization minimization (MM) and inner approximation (IA)
techniques. Simulation results unveil a non-trivial trade-off between the
considered competing objectives, as well as the superior performance of the
proposed scheme as compared to various baseline schemes.
