The purpose of this article is to model and solve an integrated location, routing and inventory problem (LRIP) in cash-in-transit (CIT) sector. In real operation of cash transportation, to decrease total cost and to reduce risk of robbery of such high-value commodity. There must be substantial variation, making problem difficult to formulate. In this paper, to better fit real life applications ...

In practice, due to the lack of information, imprecise variables which come from experts’ empirical data usually appear. In order to deal with these imprecise variables, uncertainty theory is proposed and has been proved to be an efficient method. This paper introduces uncertainty theory into travelling salesman problem (TSP), in which the link travel times are assumed to be uncertain variables...

The data envelopment analytical hierarchy process (DEAHP) is a type of the analytical hierarchy process (AHP), which used the concept of data envelopment analysis (DEA) for generating LW from the judgment matrices and aggregating them to be final weight (FW) in AHP. In general, the judgment scales in AHP is built based on decision maker. It is unrealistic to expect that the decision maker has c...

The environment of loan in bank is very complex, there are not only random factors but also fuzzy factors, so the return rates of loan often have fuzzy random characteristic. Mean chance is a measure of fuzzy random variable. This paper proposes two fuzzy random dependentchance programming models of loan portfolio, one is minimize the mean chance of a bad outcome under the certain expected retu...

Fuzzy random variable is a combination of fuzzy variable and random variable, and can characterize both fuzziness and randomness in the real world. The mean chance of a fuzzy random event is an important concept in fuzzy random optimization, just like the probability of a stochastic event in stochastic optimization and the credibility of a fuzzy event in fuzzy optimization. In fuzzy random prog...

We study a class of chance-constrained two-stage stochastic optimization problems where second-stage feasible recourse decisions incur additional cost. In addition, we propose a new model, where “recovery” decisions are made for the infeasible scenarios to obtain feasible solutions to a relaxed second-stage problem. We develop decomposition algorithms with specialized optimality and feasibility...

An exact algorithm is developed for the chance-constrained multi-area reserve sizing problem in presence of transmission network constraints. The can be cast as a two-stage stochastic mixed integer linear program using sample approximation. Due to complicated structure problem, existing methods attempt find feasible solution based on heuristics. Existing mixed-integer algorithms that applied di...