this paper investigates the problem of just-in-time permutation flow shop scheduling with limited buffers and linear job deterioration in an uncertain environment. the fuzzy set theory is applied to describe this situation. a novel mixed-integer nonlinear program is presented to minimize the weighted sum of fuzzy earliness and tardiness penalties. due to the computational complexities, the prop...

Implementations of the Simplex method differ only in very specific aspects such as the pivot rule. Similarly, most relaxation methods for mixed-integer programming differ only in the type of cuts and the exploration of the search tree. Implementing instances of those frameworks would therefore be more efficient if linear and mixed-integer programming solvers let users customize such aspects eas...

Two algorithms for the general case of parametric mixed-integer linear programs (MILPs) are proposed. Parametric MILPs are considered in which a single parameter can simultaneously influence the objective function, the right-hand side and the matrix. The first algorithm is based on branch-and-bound on the integer variables, solving a parametric linear program (LP) at each node. The second algor...

A conic integer program is an integer programming problem with conic constraints.Manyproblems infinance, engineering, statistical learning, andprobabilistic optimization aremodeled using conic constraints. Herewe studymixed-integer sets definedby second-order conic constraints.We introduce general-purpose cuts for conic mixed-integer programming based on polyhedral conic substructures of second...

in order to implement the cellular manufacturing system in practice, some essential factors should be taken into account. in this paper, a new mathematical model for cellular manufacturing system considering different production factors including alternative process routings and machine reliability with stochastic arrival and service times in a dynamic environment is proposed. also because of t...

In this paper we consider multistage stochastic programs with endogenous parameters where investment strategies are considered to reduce uncertainty, and time-varying distributions are used to describe uncertainty. We present the proposed ideas in the context of the planning of process networks with uncertain yields. We propose a new mixed-integer/disjunctive programming model which is reformul...

This work addresses the problem of synthesising cost-effective batch water networks where a number of process sources along with fresh water are mixed, stored, and assigned to process sinks. In order to address the complexity of the problem, a three-stage hierarchical approach is proposed. In the first stage, global targets are identified by formulating and solving a linear transportation probl...

Integration of scheduling and control can improve the overall performance of a manufacturing process. However, the integration leads to a mixed-integer dynamic optimization problem (MIDO), which could be challenging to solve. We propose a novel algorithm based on the generalized Bender decomposition method that takes advantage of the special structure of the integrated problem. It decomposes th...

We introduce a new way of generating cutting planes of a mixed integer programme by way of taking binary variables. Four binary variables are introduced to form quartic inequalities, which results in a reduced first-level mixed integer programme. A new way of weakening the inequalities is presented. An algorithm to carryout the separation of the inequalities, which are exponential in number, is...