data envelopment analysis (dea) is a mathematical technique to evaluate the performance of firms with multiple inputs and outputs. in conventional dea models, the efficiency scores of decision making units (dmus) with non-negative inputs and outputs are evaluated in a special period of time. however, in the real world there are situations wherein performance of firms must be evaluated in multip...

Motivated by the challenges encountered in sawmill production planning, we study a multi-product, multi-period production planning problem with uncertainty in the quality of raw materials and consequently in processes yields, as well as uncertainty in products demands. As demand and yield own different uncertain natures, they are modeled separately and then integrated. Demand uncertainty is con...

• Propose model predictive control with risk-parity objective transaction control. Derive a successive convex algorithm to efficiently solve the MPC. MPC strategies beat benchmarks in out-of-sample tests various asset universes. Multi-period planning provides advantage via over single-period planning. We employ for multi-period portfolio optimization problem. In addition mean-variance objective...

In this literature review we discuss asynchronous multi agent motion planning. We first introduce fundamental ideas related to asynchronous multi agent motion planning such as asynchronous computation, multi agent systems and motion planning. We then discuss related work in asynchronous systems and motion planning of multi agent systems. We then discuss the application of asynchronous multi age...

The paper discusses a multi-stage stochastic programming approach to the strategic ®nancial management of a multi-company ®nancial conglomerate. The planning system creates a comprehensive strategy which simultaneously covers a number of future scenarios within a multi-period planning horizon. Multiple con ̄icting goals may be speci®ed for the group level, company level or individual business ar...

The objective of this paper is to describe a method of implementing multi-period twoand multi-stage Stochastic Programming (SP) models with exogenous uncertainty that is modeling-platform and programming-language independent. The proposed implementation approach generates an implicit extensive form of the SP model in contrast to an explicit formulation, which explicitly accounts for the sequenc...

In this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. A two-stage stochastic linear programming approach is used to maximize the expected profit. Decisions such as the production amount, the inventory level of finished and semi-finished product, t...

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...

The multi-objective optimization for a multi-product multi-period four-echelon supply chain network consisting of manufacturing plants, distribution centers (DCs) and retailers each with uncertain services and uncertain customer nodes are aimed in this paper. The two objectives are minimization of the total supply chain cost and maximization of the average number of products dispatched to custo...