This paper uses the L1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (WDSND) vectorsof a multi-objective mixed integer linear programming (MOMILP) problem.The proposed method generalizes the proposed approach by Tohidi and Razavyan[Tohidi G., S. Razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...

Rapid economic development and population growth in Malaysia had accelerated the generation of solid waste. This issue gives pressure for effective management of municipal solid waste (MSW) to take place in Malaysia due to the increased cost of landfill. This paper discusses optimal planning of waste-to-energy (WTE) using a combinatorial simulation and optimization model through mixed integer l...

Constraint Programming (CP) users need significant expertise in order to model their problems appropriately, notably to select propagators and search strategies. This puts the brakes on a broader uptake of CP. In this paper, we introduce MICE, a complete Java CP modeler that can use any Mixed Integer Linear Programming (MILP) solver as a solution technique. Our aim is to provide an alternative ...

Task allocation and scheduling for heterogeneous multicore platforms must be automated for such platforms to be successful. Techniques such as Mixed Integer Linear Programming (MILP) provide the ability to easily customize the allocation and scheduling problem to application or platform-specific peculiarities. The representation of the core problem in a MILP form has a large impact on the solut...

Symmetry in mathematical optimisation is of broad and current interest. In problem classes such as mixed-integer linear programming (MILP), equivalent solutions created by symmetric variables and constraints may combinatorially increase the search space. Identifying problem symmetries is an important step towards expediting tree-based algorithms such as branch-and-cut because computationally cl...

This paper addresses the problem of developing an optimisation structure to aid the operational decision-making of scheduling activities in a real-world pipeline scenario. The pipeline connects an inland refinery to a harbour, conveying different types of oil derivatives. The optimisation structure is developed based on mixed integer linear programming (MILP) with uniform time discretisation, b...

The Resource-Constrained Project Scheduling Problem (RCPSP) and some of its extensions have been widely studied. Many approaches have been considered to solve this problem: constraint programming (CP), Boolean satisfiability (SAT), mixed integer linear programming (MILP), branch and bound algorithms (BB) and others. In this paper, we present a new approach for solving this problem: satisfiabili...

In recent years, Mixed Integer Linear Programming (MILP) has been successfully applied in searching for differential characteristics and linear approximations in block ciphers and has produced the significant results for some ciphers such as SIMON (a family of lightweight and hardware-optimized block ciphers designed by NSA) etc. However, in the literature, the MILP-based automatic search algor...

This paper presents a hybrid algorithm for optimal scheduling of multipurpose batch process plants. The algortihm decomposes the scheduling problem into two parts: an aggregate scheduling stage, based on Mixed Integer Linear Programming (MILP), and a detailed scheduling stage, applying Constraint Logic Programming (CLP). This decomposition utilises the complementary strengths of the two solutio...

Controlled tabular adjustment is an SDL methodology based on a mixed integer linear programming model. We develop new hybrid heuristics and new metaheuristic learning approaches for solving this model, and examine their performance. Our new approaches are based on partitioning the problem into its discrete and continuous components, and first creating a hybrid that reduces the number of binary ...